en,zh,source
Help,帮助,"global.R, radiant.R, manage_ui.R, pivotr_ui.R"
Normal,正态分布,"clt_ui.R,simulater_ui.R"
Binomial,二项分布,"clt_ui.R,simulater_ui.R"
Uniform,均匀分布,"clt_ui.R,simulater_ui.R"
Exponential,指数分布,clt_ui.R
Sum,求和,clt_ui.R
Mean,平均值,"clt_ui.R,sample_size_comp.R, sample_size_ui.R"
Run simulation,运行模拟,"clt_ui.R,simulater_ui.R"
Re-run simulation,重新运行模拟,"clt_ui.R,simulater_ui.R"
Distribution:,分布：,clt_ui.R
Min:,最小值：,"clt_ui.R,dtree_ui.R"
Max:,最大值：,"clt_ui.R,dtree_ui.R"
Mean:,均值：,"clt_ui.R,simulater_ui.R"
SD:,标准差：,clt_ui.R
Rate:,速率：,clt_ui.R
Size:,样本量：,"clt_ui.R,transform_ui.R, visualize_ui.R,nn_ui.R"
Prob:,概率：,clt_ui.R
Sample size:,样本大小：,"clt_ui.R,sampling_ui.R"
# of samples:,样本数量：,clt_ui.R
Number of bins:,分箱数量：,"clt_ui.R,visualize_ui.R"
Central Limit Theorem,中心极限定理,"clt_ui.R,init.R"
Basics > Probability,基础 > 概率,clt_ui.R
Please choose a sample size larger than 2,请选择一个大于 2 的样本大小,clt_ui.R
Please choose 2 or more samples,请选择 2 个或更多样本,clt_ui.R
Please choose a minimum value for the uniform distribution,请为均匀分布选择一个最小值,clt_ui.R
Please choose a maximum value for the uniform distribution,请为均匀分布选择一个最大值,clt_ui.R
The maximum value for the uniform distribution\nmust be larger than the minimum value,均匀分布的最大值必须大于最小值,clt_ui.R
Please choose a mean value for the normal distribution,请为正态分布选择一个均值,clt_ui.R
Please choose a non-zero standard deviation for the normal distribution,请为正态分布选择一个非零的标准差,clt_ui.R
Please choose a rate larger than 1 for the exponential distribution,请为指数分布选择一个大于 1 的速率,clt_ui.R
Please choose a size parameter larger than 1 for the binomial distribution,请为二项分布选择一个大于 1 的大小参数,clt_ui.R
Please choose a probability between 0 and 1 for the binomial distribution,请为二项分布选择一个介于 0 到 1 之间的概率,clt_ui.R
** Press the Run simulation button to simulate data **,** 请点击“运行模拟”按钮以生成数据 **,"clt_ui.R,simulater_ui.R"
Generating plots,正在生成图形,"clt_ui.R, compare_means_ui.R,crs_ui.R, crtree_ui.R, gbt_ui.R, logistic_ui.R,conjoint_ui.R, kclus_ui.R"
Save central limit theorem plot,保存中心极限定理图,clt_ui.R
Two sided,双尾检验,"compare_means_ui.R,sample_size_comp.R"
Less than,小于,compare_means_ui.R
Greater than,大于,compare_means_ui.R
independent,独立样本,compare_means_ui.R
paired,配对样本,compare_means_ui.R
None,无,"compare_means_ui.R,pivotr_ui.R,crtree_ui.R, gbt_ui.R,conjoint_ui.R"
Bonferroni,Bonferroni 校正,compare_means_ui.R
Scatter,散点图,"compare_means_ui.R,visualize_ui.R,logistic_ui.R,kclus_ui.R"
Box,箱线图,compare_means_ui.R
Density,密度图,"compare_means_ui.R,visualize_ui.R,kclus_ui.R"
Bar,条形图,"compare_means_ui.R,visualize_ui.R,kclus_ui.R"
Select a factor or numeric variable:,选择一个因子或数值变量：,compare_means_ui.R
Numeric variable(s):,数值变量(多选)：,"compare_means_ui.R,explore_ui.R"
Numeric variable:,数值变量：,"compare_means_ui.R,pivotr_ui.R"
Choose combinations:,选择组合：,compare_means_ui.R
Evaluate all combinations,评估所有组合,compare_means_ui.R
Alternative hypothesis:,备择假设：,"compare_means_ui.R,sample_size_comp.R"
Confidence level:,置信水平：,"compare_means_ui.R,sample_size_comp.R, sample_size_ui.R,logistic_ui.R"
Show additional statistics,显示额外统计量,compare_means_ui.R
Sample type:,样本类型：,compare_means_ui.R
Multiple comp. adjustment:,多重比较校正：,compare_means_ui.R
Test type:,检验类型：,compare_means_ui.R
t-test,t 检验,compare_means_ui.R
Wilcox,Wilcoxon 检验,compare_means_ui.R
Select plots:,选择绘图类型：,compare_means_ui.R
Select plots,选择绘图,compare_means_ui.R
Compare means,均值比较,"compare_means_ui.R,init.R"
Summary,摘要,"compare_means_ui.R,doe_ui.R, randomizer_ui.R, sample_size_comp.R, sample_size_ui.R, sampling_ui.R,gbt_ui.R,conjoint_ui.R"
Plot,图形,"compare_means_ui.R,sample_size_comp.R,dtree_ui.R, gbt_ui.R,conjoint_ui.R"
Basics > Means,基础 > 均值,compare_means_ui.R
"This analysis requires at least two variables. The first can be of type
factor, numeric, or interval. The second must be of type numeric or interval.
If these variable types are not available please select another dataset.

","该分析至少需要两个变量。第一个变量可以是因子、数值或区间类型，第二个变量必须是数值或区间类型。如果这些类型的变量不可用，请选择其他数据集。
",compare_means_ui.R
Nothing to plot. Please select a plot type,没有可绘制的内容，请选择绘图类型,compare_means_ui.R
Save compare means plot,保存均值比较图,compare_means_ui.R
Basics > Proportions,基础 > 比例,compare_props_ui.R
Compare proportions,比较比例,"compare_props_ui.R,init.R"
"This analysis requires two categorical variables. The first must have
two or more levels. The second can have only two levels. If these
variable types are not available please select another dataset.

","该分析需要两个分类变量。第一个变量必须具有两个或更多水平，第二个变量只能有两个水平。如果这些变量类型不可用，请选择其他数据集。
",compare_props_ui.R
Select a grouping variable:,选择分组变量：,compare_props_ui.R
Save compare proportions plot,保存比较比例图,compare_props_ui.R
Dodge,并列柱状图,compare_props_ui.R
Variable (select one):,变量（选择一个）：,compare_props_ui.R
Pearson,皮尔逊积矩相关,correlation_ui.R
Spearman,斯皮尔曼秩相关,correlation_ui.R
Kendall,肯德尔秩相关,correlation_ui.R
Calculate correlation,计算相关性,correlation_ui.R
Basics > Tables,基础 > 表格,correlation_ui.R
Correlation,相关性,"correlation_ui.R,init.R"
Adjust for {factor} variables,针对 {factor} 变量进行调整,"correlation_ui.R,full_factor_ui.R"
Calculate adjusted p.values,计算调整后的 p 值,correlation_ui.R
Correlation cutoff:,相关性阈值:,correlation_ui.R
Show covariance matrix,显示协方差矩阵,correlation_ui.R
Store,存储,"correlation_ui.R,explore_ui.R, pivotr_ui.R, view_ui.R,randomizer_ui.R, sampling_ui.R,crs_ui.R, gbt_ui.R, logistic_ui.R,conjoint_ui.R"
"This analysis requires two or more variables or type numeric, integer,or date. If these variable types are not available please select another dataset.",该分析需要两个或以上的数值型、整数型或日期型变量。如果这些变量类型不可用，请选择其他数据集。,correlation_ui.R
Method:,方法:,"correlation_ui.R,full_factor_ui.R"
Acquiring variable information,正在获取变量信息,"correlation_ui.R,pivotr_ui.R,crtree_ui.R, evalbin_ui.R, evalreg_ui.R, gbt_ui.R, logistic_ui.R"
Select variables:,选择变量:,"correlation_ui.R,transform_ui.R"
Store as data.frame:,存储为数据框:,correlation_ui.R
"This analysis requires two or more variables or type numeric,\ninteger,or date. If these variable types are not available\nplease select another dataset.\n\n",本分析需要两个或以上的变量，并且类型必须是数值型、整数型或日期型。如果这些变量类型不可用，请选择其他数据集。,correlation_ui.R
Save correlation plot,保存相关性图表,correlation_ui.R
Number of data points plotted:,绘制的数据点数量：,"correlation_ui.R,visualize_ui.R,crtree_ui.R, gbt_ui.R, logistic_ui.R"
"This analysis requires two or more variables or type numeric,
integer,or date. If these variable types are not available
please select another dataset.

","本分析需要两个或以上的变量，并且类型必须是数值型、整数型或日期型。
如果这些变量类型不可用，请选择其他数据集。
",correlation_ui.R
Re-calculate correlations,重新计算相关系数,correlation_ui.R
Observed,观察值,cross_tabs_ui.R
Expected,期望值,cross_tabs_ui.R
Chi-squared,卡方值,cross_tabs_ui.R
Deviation std.,标准差偏差,cross_tabs_ui.R
Row percentages,行百分比,cross_tabs_ui.R
Column percentages,列百分比,cross_tabs_ui.R
Table percentages,表格百分比,cross_tabs_ui.R
Cross-tabs,交叉表,"cross_tabs_ui.R,init.R"
"This analysis requires two categorical variables. Both must have two or more levels.
If these variable types are not available please select another dataset.

","此分析需要两个分类变量，且每个变量必须至少有两个水平。如果这些类型的变量不可用，请选择其他数据集。
",cross_tabs_ui.R
Select a categorical variable:,请选择一个分类变量：,cross_tabs_ui.R
Save cross-tabs plot,保存交叉表图形,cross_tabs_ui.R
Goodness of fit,拟合优度检验,"goodness_ui.R,init.R"
"This analysis requires a categorical variables with two or more levels.
If such a variable type is not available please select another dataset.

","此分析需要一个具有两个或以上水平的分类变量。如果没有这种类型的变量，请选择其他数据集。
",goodness_ui.R
Save goodness of fit plot,保存拟合优度检验图形,goodness_ui.R
Probabilities:,概率：,"goodness_ui.R,randomizer_ui.R"
"Enter probabilities (e.g., 1/2 1/2)",输入概率（例如：1/2 1/2）,"goodness_ui.R,randomizer_ui.R"
Discrete,离散分布,"prob_calc_ui.R,simulater_ui.R"
F,F 分布,prob_calc_ui.R
Log normal,对数正态分布,"prob_calc_ui.R,simulater_ui.R"
Poisson,泊松分布,"prob_calc_ui.R,simulater_ui.R"
Values,数值,prob_calc_ui.R
Probability calculator,概率计算器,"prob_calc_ui.R,init.R"
Input type:,输入类型：,prob_calc_ui.R
Decimals:,小数位数：,"prob_calc_ui.R,explore_ui.R, pivotr_ui.R, view_ui.R,simulater_ui.R"
Save probability calculator plot,保存概率计算器图形,prob_calc_ui.R
Please provide a mean and standard deviation (> 0),请提供平均值和标准差（标准差需大于 0）,prob_calc_ui.R
St. dev:,标准差：,prob_calc_ui.R
Lower bound:,下限：,prob_calc_ui.R
Upper bound:,上限：,prob_calc_ui.R
Provide an integer value for the number of decimal places,请输入整数，表示保留的小数位数,prob_calc_ui.R
"Please provide a set of values and probabilities.
Separate numbers using spaces (e.g., 1/2 1/2)",请提供一组数值和对应的概率。\n请用空格分隔（例如：1/2 1/2）,prob_calc_ui.R
Values:,数值：,"prob_calc_ui.R,simulater_ui.R"
Please provide a value for n (number of trials) and p (probability of success),请提供试验次数 (n) 和成功概率 (p) 的值,prob_calc_ui.R
Please provide a minimum and a maximum value,请提供最小值和最大值,prob_calc_ui.R
Please provide a value for the degrees of freedom (> 0),请提供大于 0 的自由度值,prob_calc_ui.R
"Please provide a value for Degrees of freedom 1 (> 0)
and for Degrees of freedom 2 (> 4)",请提供自由度 1（大于 0）和自由度 2（大于 4）的值,prob_calc_ui.R
Please provide a value for the rate (> 0),请提供大于 0 的速率值,prob_calc_ui.R
Please provide a value for lambda (> 0),请提供大于 0 的 λ（Lambda）值,prob_calc_ui.R
n:,试验次数：,"prob_calc_ui.R,simulater_ui.R"
p:,成功概率：,"prob_calc_ui.R,simulater_ui.R"
Degrees of freedom:,自由度：,prob_calc_ui.R
Degrees of freedom 1:,自由度 1：,prob_calc_ui.R
Degrees of freedom 2:,自由度 2：,prob_calc_ui.R
Mean log:,对数均值：,prob_calc_ui.R
St. dev log:,对数标准差：,prob_calc_ui.R
Lambda:,λ：,"prob_calc_ui.R,kclus_ui.R,simulater_ui.R"
Histogram,直方图,single_mean_ui.R
Simulate,模拟,"single_mean_ui.R,simulater_ui.R,init.R"
Single mean,单样本均值,"single_mean_ui.R,init.R"
Comparison value:,比较值：,single_mean_ui.R
"This analysis requires a variable of type numeric or interval. If none are
available please select another dataset.

","此分析需要一个数值型或区间型变量。如果当前数据集中没有此类变量，请选择其他数据集。
",single_mean_ui.R
Save single mean plot,保存单样本均值图表,single_mean_ui.R
Single proportion,单样本比例,"single_prop_ui.R,init.R"
Binomial exact,精确二项检验,single_prop_ui.R
Z-test,Z 检验,single_prop_ui.R
Choose level:,选择水平：,"single_prop_ui.R,crtree_ui.R, evalbin_ui.R, logistic_ui.R"
"This analysis requires a categorical variable. In none are available
please select another dataset.

","本分析需要一个分类变量。如果没有可用的分类变量，请选择其他数据集。
",single_prop_ui.R
Save single proportion plot,保存单样本比例图,single_prop_ui.R
Keyboard shortcuts,键盘快捷键,"global.R, manage_ui.R,help.R"
Combine with:,合并对象：,combine_ui.R
Join by:,按以下字段连接：,combine_ui.R
Variables to add:,要追加的变量：,combine_ui.R
Inner join,内连接,combine_ui.R
Left join,左连接,combine_ui.R
Right join,右连接,combine_ui.R
Full join,全连接,combine_ui.R
Semi join,半连接,combine_ui.R
Anti join,反连接,combine_ui.R
Bind rows,按行合并,combine_ui.R
Bind columns,按列合并,combine_ui.R
Intersect,交集,combine_ui.R
Union,并集,combine_ui.R
Set difference,差集,combine_ui.R
Combine,合并,"combine_ui.R, data_ui.R"
Only one dataset available.,仅有一个数据集，无法合并。,combine_ui.R
Combine type:,合并方式：,combine_ui.R
Combined dataset:,合并后数据集：,combine_ui.R
<label>Only one dataset available.</label>,<label>仅有一个数据集，无法合并。</label>,combine_ui.R
<h3>Dataset 1:,<h3>数据集 1：,combine_ui.R
<h3>Dataset 2:,<h3>数据集 2：,combine_ui.R
<h3>No matching variables selected</h3>,<h3>未选择可匹配字段</h3>,combine_ui.R
"</br><h4>Combining data failed. The error message was:</br></br>\"",</br><h4>合并数据失败，错误信息如下：</br></br>\""""",combine_ui.R,
<h3>Combined dataset: ,<h3>合并后数据集：,combine_ui.R
Filter data,筛选数据,data_ui
Data filter:,数据筛选：,data_ui
"Provide a filter (e.g., price >  5000) and press return",输入筛选条件（例如 price > 5000）并按回车,data_ui
Data arrange (sort):,数据排序：,data_ui
"Arrange (e.g., color, desc(price)) and press return","输入排序方式（例如 color, desc(price)）并按回车",data_ui
Data slice (rows):,数据行截取：,data_ui
Manage,管理,data_ui
Data preview,数据预览,data_ui
Data structure,数据结构,data_ui
Data summary,数据摘要,data_ui
Data load and save commands,数据加载与保存命令,data_ui
View,查看,"data_ui, view_ui.R"
Visualize,可视化,"data_ui, visualize_ui.R"
Pivot,透视表,data_ui
Explore,探索,"data_ui, explore_ui.R"
Transform,转换,data_ui
Group by:,分组变量：,"explore_ui.R, pivotr_ui.R,simulater_ui.R"
Select group-by variable,选择分组变量,"explore_ui.R,simulater_ui.R"
Apply function(s):,应用函数：,explore_ui.R
Select functions,选择函数,explore_ui.R
Function,函数,"explore_ui.R,help.R"
Variables,变量,explore_ui.R
Group by,分组,explore_ui.R
Column header:,列标题：,explore_ui.R
Store as:,存储为：,"explore_ui.R, pivotr_ui.R,randomizer_ui.R, sampling_ui.R"
Provide a table name,请输入表格名称,"explore_ui.R, pivotr_ui.R,evalbin_ui.R"
Create table,生成表格,explore_ui.R
Update table,更新表格,explore_ui.R
Table slice (rows):,表格行选择：,"explore_ui.R, pivotr_ui.R, view_ui.R"
"e.g., 1:50 and press return",例如 1:5 并按回车,"explore_ui.R, data_ui"
Generating explore table,正在生成探索表格,explore_ui.R
Data Stored,数据已保存,"explore_ui.R, pivotr_ui.R, view_ui.R,randomizer_ui.R, sampling_ui.R,crs_ui.R"
Dataset was successfully added to the datasets dropdown. Add code to Report > Rmd or Report > R to (re)create the results by clicking the report icon on the bottom left of your screen.,数据集已成功添加到下拉菜单中。点击左下角的报告图标，在 报告 > Rmd 或 报告 > R 中添加代码以（重新）生成结果。,explore_ui.R
OK,确定,"explore_ui.R, manage_ui.R, pivotr_ui.R,randomizer_ui.R, sampling_ui.R,crs_ui.R, evalbin_ui.R"
Load radiant state file,加载 Radiant 状态文件,"manage_ui.R,global.R"
Load,加载,manage_ui.R
Load data,加载数据,manage_ui.R
Description,描述,manage_ui.R
Paste,粘贴,manage_ui.R
Copy data,复制数据,manage_ui.R
Save,保存,"manage_ui.R,logistic_ui.R,radiant.R"
Save data,保存数据,manage_ui.R
Save radiant state file,保存 Radiant 状态文件,"manage_ui.R,global.R"
Add/edit data description,添加/编辑数据描述,manage_ui.R
Rename data,重命名数据,manage_ui.R
Display:,显示：,manage_ui.R
Show R-code,显示 R 代码,manage_ui.R
Remove data from memory,从内存中移除数据,manage_ui.R
Remove data,移除数据,manage_ui.R
Copy-and-paste data below:,复制并粘贴数据到下方：,manage_ui.R
Data.frames in Global Env:,全局环境中的数据框：,manage_ui.R
to global workspace,到全局工作空间,manage_ui.R
rds | rda | rdata,rds | rda | rdata,manage_ui.R
parquet,列式存储,manage_ui.R
csv,csv,manage_ui.R
clipboard,剪贴板,transform_ui.R
Clipboard,剪贴板,"manage_ui.R,transform_ui.R"
examples,示例,manage_ui.R
rds (url),rds（url）,manage_ui.R
csv (url),csv（url）,manage_ui.R
from global workspace,从全局工作空间,manage_ui.R
radiant state file,Radiant 状态文件,manage_ui.R
rds,rds,manage_ui.R
rda,rda,manage_ui.R
<label>Load radiant state file:</label></br>, "<label>加载 Radiant 状态文件：</label></br>", "manage_ui.R"
Upload radiant state file:, "上传 Radiant 状态文件：", "manage_ui.R"
, "", "manage_ui.R"
Datasets:, "数据集：", "manage_ui.R"
Update description, "更新描述", "manage_ui.R"
Load data of type:, "加载数据类型：", "data_ui"
Header, "表头", "data_ui"
Str. as Factor, "作为因子处理字符串", "data_ui"
Separator:, "分隔符：", "data_ui"
Decimal:, "小数点：", "data_ui"
Maximum rows to read:, "最大读取行数：", "data_ui"
Save data to type:, "保存数据类型：", "manage_ui.R"
<label>Save radiant state file:</label><br/>, "<label>保存 Radiant 状态文件：</label><br/>", "manage_ui.R"
## Load commands, "## 加载命令", "manage_ui.R"
diamonds, "钻石数据集", "manage_ui.R"
<label>Add data description:</label><br>, "<label>添加数据描述：</label><br>", "manage_ui.R"
Type text to describe the data using markdown to format it.\nSee http://commonmark.org/help/ for more information, "使用 Markdown 格式化文本来描述数据。更多信息请参见 http://commonmark.org/help/", "manage_ui.R"
preview,预览,manage_ui.R
str,结构,manage_ui.R
summary,总结,manage_ui.R
#### There was an error loading the data. Please make sure the data are in csv format,#### 加载数据时发生错误。请确保数据为 CSV 格式。,manage.R
Read issues (max 10 rows shown):,读取问题（最多显示 10 行）：,manage.R
#### Radiant does not load xls files directly. Please save the data as a csv file and try again.,#### Radiant 不支持直接加载 XLS 文件。请将数据另存为 CSV 文件后再试。,manage.R
#### The filename extension \{fext}\" does not match the specified file-type \"{ext}\". Please specify the file type you are trying to upload",#### 文件扩展名“{fext}”与所选的文件类型“{ext}”不匹配。请确认要上传的文件类型。,manage.R
#### There was an error loading the data. Please make sure the data are in rda format.,#### 加载数据时发生错误。请确保数据为 RDA 格式。,manage.R
#### To restore state select 'radiant state file' from the 'Load data of type' drowdown before loading the file,#### 如需恢复状态，请先在“数据类型”下拉菜单中选择“Radiant 状态文件”后再加载。,manage.R
#### More than one R object contained in the data.,#### 数据中包含多个 R 对象。,manage.R
#### There was an error loading the data. Please make sure the data are in rds format.,#### 加载数据时发生错误。请确保数据为 RDS 格式。,manage.R
The 'arrow' package is not installed. Please install it and try again.,未安装 'arrow' 包。请先安装后再试。,manage.R
#### The arrow package required to work with data in parquet format is not installed. Please use install.packages('arrow'),#### 加载 Parquet 格式数据需要安装 arrow 包。请运行 install.packages('arrow') 进行安装。,manage.R
#### There was an error loading the data. Please make sure the data are in parquet format.,#### 加载数据时发生错误。请确保数据为 Parquet 格式。,manage.R
#### There was an error loading the data,#### 加载数据时发生错误,manage.R
#### The selected filetype is not currently supported ({fext}),#### 当前不支持所选文件类型（{fext}）,manage.R
Row,行,pivotr_ui.R
Column,列,pivotr_ui.R
Total,总计,pivotr_ui.R
Color bar,色条,pivotr_ui.R
Heat map,热力图,pivotr_ui.R
Categorical variables:,分类变量：,pivotr_ui.R
Select categorical variables,选择分类变量,pivotr_ui.R
Select numeric variable,选择数值变量,pivotr_ui.R
Apply function:,应用函数：,"pivotr_ui.R,simulater_ui.R"
Normalize by:,归一化方式：,pivotr_ui.R
Conditional formatting:,条件格式化：,pivotr_ui.R
Create pivot table,生成透视表,pivotr_ui.R
Update pivot table,更新透视表,pivotr_ui.R
"e.g., 1:5 and press return",例如：1:5 并按回车,pivotr_ui.R
Show table  ,显示表格,pivotr_ui.R
Show plot  ,显示图形,pivotr_ui.R
Percentage,百分比,pivotr_ui.R
Chi-square,卡方检验,pivotr_ui.R
Fill,填充,pivotr_ui.R
Flip,翻转,"pivotr_ui.R,visualize_ui.R"
Pivotr,透视表模块,pivotr_ui.R
Generating pivot table,正在生成透视表,pivotr_ui.R
Plots created for at most 3 categorical variables,最多只能为三个分类变量生成图表,pivotr_ui.R
Dataset '%s' was successfully added to the datasets dropdown. Add code to Report > Rmd or Report > R to (re)create the results by clicking the report icon on the bottom left of your screen.,数据集「%s」已成功添加至下拉菜单。点击左下角的报告图标可将代码添加到 Report > Rmd 或 Report > R，以用于（重新）生成结果。,"pivotr_ui.R,randomizer_ui.R, sampling_ui.R"
Making plot,正在生成图表,"pivotr_ui.R,dtree_ui.R"
Save pivot plot,保存透视图,pivotr_ui.R
Plot type:,图类型：,pivotr_ui.R
Select variable(s):,选择变量：,transform_ui.R
Normalizing variable:,标准化变量：,transform_ui.R
Frequency variable:,频率变量：,transform_ui.R
Key name:,键名：,transform_ui.R
Value name:,值名：,transform_ui.R
Key(s):,键(s)：,transform_ui.R
Value:,值：,"transform_ui.R,simulater_ui.R"
Fill:,填充:,"transform_ui.R, visualize_ui.R"
Reorder/remove variables:,重新排序/移除变量：,transform_ui.R
Select a single variable of type factor or character,选择一个类型为因子或字符的单个变量,transform_ui.R
Reorder/remove levels:,重新排序/移除级别：,transform_ui.R
Replacement level name:,替换级别名称,transform_ui.R
Variable name extension:,变量名扩展：,transform_ui.R
Recoded variable name:,重新编码变量名：,transform_ui.R
Variable name:,变量名：,"transform_ui.R,doe_ui.R"
Add extension to variable name,为变量名添加扩展,transform_ui.R
Rename variable(s):,重命名变量：,transform_ui.R
Create:,创建：,transform_ui.R
Nr bins:,箱数：,transform_ui.R
Reverse order,反转顺序,transform_ui.R
Seed:,种子:,"transform_ui.R,crtree_ui.R, gbt_ui.R"
Reverse filter and slice,反向过滤并切片,transform_ui.R
Paste from spreadsheet:,从电子表格粘贴：,transform_ui.R
"Specify a recode statement, assign a name to the recoded variable, and press 'return'",指定重新编码语句，为重新编码的变量分配名称，并按回车,transform_ui.R
Select one or more variables to rename,选择一个或多个变量进行重命名,transform_ui.R
Select one or more variables to replace,选择一个或多个变量进行替换,transform_ui.R
Select a variable to recode,选择一个变量进行重新编码,transform_ui.R
Select one or more variables to bin,选择一个或多个变量进行分箱,transform_ui.R
Select a single variable of type factor to change the ordering and/or number of levels,选择一个因子类型的单个变量来更改排序和/或级别数量,transform_ui.R
Select one or more variables to normalize,选择一个或多个变量进行标准化,transform_ui.R
Select one or more variables to see the effects of removing missing values,选择一个或多个变量，查看移除缺失值的效果,transform_ui.R
Select one or more variables to see the effects of removing duplicates,选择一个或多个变量，查看移除重复值的效果,transform_ui.R
Select one or more variables to gather,选择一个或多个变量进行汇集,transform_ui.R
Select one or more variables to expand,选择一个或多个变量进行扩展,transform_ui.R
Select a transformation type or select variables to summarize,选择一个转换类型或选择变量进行汇总,transform_ui.R
The transformation type you selected generated an error.,您选择的转换类型生成了一个错误。,transform_ui.R
The error message was:,错误消息是：,transform_ui.R
Please change the selection of variables or the transformation type and try again.,请更改变量选择或转换类型并重试。,transform_ui.R
The create command was not valid.,创建命令无效。,transform_ui.R
The command entered was:,输入的命令是：,transform_ui.R
Please try again. Examples are shown in the help file (click the ? icon).,请再试一次。示例已显示在帮助文件中（点击？图标）,transform_ui.R
Some of the variables names used are not valid. Please use 'Rename' to ensure variable names do not have any spaces or symbols and start with a letter,使用的变量名中有些无效。请使用“重命名”确保变量名没有空格或符号，并以字母开头,transform_ui.R
No duplicates found (n_distinct = ,未找到重复项（n_distinct = ,transform_ui.R
## remove missing values,## 移除缺失值,transform_ui.R
## remove duplicate rows,## 移除重复行,transform_ui.R
## show duplicate rows,## 显示重复行,transform_ui.R
## change variable type,## 更改变量类型,transform_ui.R
## transform variable,## 转换变量,transform_ui.R
## created variable to select training sample,## 创建变量来选择训练样本,transform_ui.R
## create new variable,## 创建新变量,transform_ui.R
## rename variable,## 重命名变量,transform_ui.R
## reorder/remove variables,## 重新排序/移除变量,transform_ui.R
## change factor levels,## 更改因子级别,transform_ui.R
## bin variables,## 分箱变量,transform_ui.R
## gather columns,## 汇集列,transform_ui.R
## spread columns,## 扩展列,transform_ui.R
## create holdout sample,## 创建保留样本,transform_ui.R
## register the new dataset,## 注册新数据集,transform_ui.R
Ln (natural log),自然对数,transform_ui.R
Square,平方,transform_ui.R
Square‑root,平方根,transform_ui.R
Center,居中,"transform_ui.R,logistic_ui.R"
Standardize,标准化,"transform_ui.R,logistic_ui.R,hclus_ui.R"
Inverse,逆,transform_ui.R
As factor,作为因子,transform_ui.R
As numeric,作为数值,transform_ui.R
As integer,作为整数,transform_ui.R
As character,作为字符,transform_ui.R
As time series,作为时间序列,transform_ui.R
As date (mdy),作为日期（mdy）,transform_ui.R
As date (dmy),作为日期（dmy）,transform_ui.R
As date (ymd),作为日期（ymd）,transform_ui.R
As date/time (mdy_hms),作为日期时间（mdy_hms）,transform_ui.R
As date/time (mdy_hm),作为日期时间（mdy_hm）,transform_ui.R
As date/time (dmy_hms),作为日期时间（dmy_hms）,transform_ui.R
As date/time (dmy_hm),作为日期时间（dmy_hm）,transform_ui.R
As date/time (ymd_hms),作为日期时间（ymd_hms）,transform_ui.R
As date/time (ymd_hm),作为日期时间（ymd_hm）,transform_ui.R
None (summarize),无（汇总）,transform_ui.R
Bin,分箱,transform_ui.R
Change type,更改类型,transform_ui.R
Remove/reorder levels,移除/重新排序级别,transform_ui.R
Rename,重命名,transform_ui.R
Create,创建,transform_ui.R
Remove missing values,移除缺失值,transform_ui.R
Remove/reorder variables,移除/重新排序变量,transform_ui.R
Remove duplicates,移除重复值,transform_ui.R
Show duplicates,显示重复值,transform_ui.R
Expand grid,扩展网格,transform_ui.R
Table‑to‑data,表格转数据,transform_ui.R
Holdout sample,保留样本,transform_ui.R
Training variable,训练变量,transform_ui.R
Gather columns,汇集列,transform_ui.R
Spread column,扩展列,transform_ui.R
Transform command log:,转换命令日志：,transform_ui.R
Generating summary statistics,生成摘要统计,transform_ui.R
Hide summaries,隐藏摘要,transform_ui.R
Transformation type:,转换类型：,transform_ui.R
Change variable type:,更改变量类型：,transform_ui.R
Start year:,起始年份：,transform_ui.R
Start period:,起始周期：,transform_ui.R
End year:,结束年份：,transform_ui.R
End period:,结束周期：,transform_ui.R
Frequency:,频率：,transform_ui.R
"Type a formula to create a new variable (e.g., x = y - z) and press return",输入公式以创建新变量（例如 x = y - z）并按回车,transform_ui.R
Copy-and-paste data with a header row from a spreadsheet,从电子表格复制并粘贴带有标题行的数据,transform_ui.R
Recode,重编码,transform_ui.R
"Select a variable, specify how it should be recoded (e.g., lo:20 = 0; else = 1), and press return",选择一个变量，指定如何重新编码（例如 lo:20 = 0；else = 1），并按回车,transform_ui.R
Store changes in:,将更改存储在：,transform_ui.R
Select variables to show:,选择要显示的变量：,view_ui.R
Clear settings,清除设置,view_ui.R
Store filtered data as:,将筛选后的数据存储为：,view_ui.R
Dataset '{dataset}' was successfully added to the datasets dropdown. Add code to Report > Rmd or Report > R to (re)create the dataset by clicking the report icon on the bottom left of your screen.,数据集'{dataset}'已成功添加到数据集下拉菜单中。点击左下角的报告图标，在Report > Rmd或Report > R中添加代码以（重新）创建该数据集。,view_ui.R
Generating view table,正在生成查看表格,view_ui.R
_view,_视图,view_ui.R
Provide data name,提供数据名称,"view_ui.R,crs_ui.R,conjoint_ui.R"
All,全部,"view_ui.R,evalbin_ui.R, evalreg_ui.R"
"Table slice {input$view_tab_slice} will be applied on Download, Store, or Report",表格切片 {input$view_tab_slice} 将应用于下载、存储或报告,view_ui.R
Dataset ',数据集 ',view_ui.R
' was successfully added to the datasets dropdown. Add code to Report > Rmd or Report > R to (re)create the dataset by clicking the report icon on the bottom left of your screen.,' 已成功添加到数据集下拉菜单中。通过点击左下角的报告图标，在 Report > Rmd 或 Report > R 中添加代码以（重新）创建数据集。,view_ui.R
Distribution,分布,"visualize_ui.R,logistic_ui.R"
Surface,表面图,visualize_ui.R
Line,折线图,"visualize_ui.R,regress_ui.R"
Box-plot,箱线图,visualize_ui.R
Loess,局部加权回归,"visualize_ui.R,regress_ui.R"
Jitter,抖动,"visualize_ui.R,regress_ui.R"
Interpolate,插值,visualize_ui.R
Log X,对数X,visualize_ui.R
Log Y,对数Y,visualize_ui.R
Scale-y,缩放Y,visualize_ui.R
Sort,排序,visualize_ui.R
Gray,灰色,visualize_ui.R
Black and White,黑白,visualize_ui.R
Light,浅色,visualize_ui.R
Dark,深色,visualize_ui.R
Minimal,简约,visualize_ui.R
Classic,经典,visualize_ui.R
title,标题,visualize_ui.R
subtitle,副标题,visualize_ui.R
caption,说明,visualize_ui.R
x,X轴,visualize_ui.R
y,Y轴,visualize_ui.R
Theme default,默认字体,visualize_ui.R
Helvetica,Helvetica字体,visualize_ui.R
Serif,衬线字体,visualize_ui.R
Sans,无衬线字体,visualize_ui.R
Mono,等宽字体,visualize_ui.R
Courier,Courier字体,visualize_ui.R
Times,Times字体,visualize_ui.R
dataset, "数据集", "visualize_ui.R"
data_filter, "数据筛选", "visualize_ui.R"
arr, "排序", "visualize_ui.R"
rows, "行", "visualize_ui.R"
labs, "标签", "visualize_ui.R"
Plot-type:, "绘图类型:", "visualize_ui.R"
Y-variable:, "Y变量:", "visualize_ui.R"
X-variable:, "X变量:", "visualize_ui.R"
Combine Y-variables in one plot, "将Y变量合并到一个图表中", "visualize_ui.R"
Combine X-variables in one plot, "将X变量合并到一个图表中", "visualize_ui.R"
Facet row:, "分面行:", "visualize_ui.R"
Facet column:, "分面列:", "visualize_ui.R"
Color:, "颜色", "visualize_ui.R"
Main, "主要", "visualize_ui.R"
Function:, "函数:", "visualize_ui.R"
Labels, "标签", "visualize_ui.R"
Style, "样式", "visualize_ui.R"
Plot theme:, "图表主题:", "visualize_ui.R"
Base font size:, "基本字体大小:", "visualize_ui.R"
Font family:, "字体系列:", "visualize_ui.R"
Opacity:, "透明度:", "visualize_ui.R"
Plot height:, "图表高度:", "visualize_ui.R"
Plot width:, "图表宽度:", "visualize_ui.R"
Smooth:, "平滑:", "visualize_ui.R"
Create plot, "创建图表", "visualize_ui.R"
Update plot, "更新图表", "visualize_ui.R"
Save visualize plot, "保存可视化图表", "visualize_ui.R"
Please select variables from the dropdown menus to create a plot, "请选择下拉菜单中的变量以创建图表", "visualize_ui.R"
No Y-variable provided for a plot that requires one, "没有提供Y变量，无法绘制需要Y变量的图表", "visualize_ui.R"
Title, "标题", "visualize_ui.R"
Subtitle, "副标题", "visualize_ui.R"
Caption, "说明", "visualize_ui.R"
Y-label, "Y轴标签", "visualize_ui.R"
X-label, "X轴标签", "visualize_ui.R"
Fill color:, "填充颜色:", "visualize_ui.R"
Line color:, "线条颜色:", "visualize_ui.R"
Point color:, "点的颜色:", "visualize_ui.R"
Rnd. seed:,随机种子：,"doe_ui.R, randomizer_ui.R, sampling_ui.R"
Interactions:,交互：,"doe_ui.R,conjoint_ui.R,logistic_ui.R"
Level :,水平 ：,doe_ui.R
Create design,生成设计,doe_ui.R
Max levels:,最大水平数：,doe_ui.R
# trials:,试验次数：,doe_ui.R
"Upload an experimental design using the 'Upload factors' button or create a new design using the inputs on the left of the screen. For help, click the ? icon on the bottom left of the screen",使用“上传因素”按钮上传实验设计，或通过页面左侧的输入创建新设计。如需帮助，请点击左下角的？图标。,doe_ui.R
Add variable,添加变量,"doe_ui.R,dtree_ui.R, simulater_ui.R"
Remove variable,移除变量,"doe_ui.R,simulater_ui.R"
Partial,部分,doe_ui.R
Full,全部,doe_ui.R
Factors,因素,doe_ui.R
Upload factors:,上传因素：,doe_ui.R
Upload DOE factors,上传实验因素,doe_ui.R
Save factorial design:,保存实验设计：,doe_ui.R
Save factors:,保存因素：,doe_ui.R
Design factors:,实验因素,doe_ui.R
Generated experimental design:,生成的实验设计：,doe.R
Level 1:,水平 1：,doe_ui.R
Level 2:,水平 2：,doe_ui.R
Design > DOE,设计 > 实验设计,doe_ui.R
Design of Experiments,实验设计,"doe_ui.R,init.R"
Variables:,变量：,"randomizer_ui.R, sampling_ui.R,full_factor_ui.R"
Blocking variables:,分组变量：,randomizer_ui.R
Select blocking variables,选择分组变量,randomizer_ui.R
Condition labels:,条件标签：,randomizer_ui.R
Provide a name,请输入名称,"randomizer_ui.R, sampling_ui.R"
Assign conditions,分配条件,randomizer_ui.R
Re-assign conditions,重新分配条件,randomizer_ui.R
Design > Sample,设计 > 抽样,"randomizer_ui.R, sample_size_comp.R, sample_size_ui.R, sampling_ui.R"
Random assignment,随机分配,"randomizer_ui.R,init.R"
Save random assignment,保存随机分配,randomizer_ui.R
"For random assignment each row in the data should be distinct (i.e., no duplicates). Please select an appropriate dataset.","每条记录都应唯一（无重复）。请选择合适的数据集。
",randomizer_ui.R
Type condition labels separated by comma's and press return,输入条件标签（用逗号分隔），然后按回车,randomizer_ui.R
Condition variable name:,条件变量名：,randomizer_ui.R
Provide a variable name,请输入变量名,randomizer_ui.R
Sample size (compare),样本量（比较）,"sample_size_comp_ui.R,init.R"
Sample size (n1):,样本量 (n1):,sample_size_comp.R
Sample size (n2):,样本量 (n2):,sample_size_comp.R
Proportion:,比例,"sample_size_comp.R, sample_size_ui.R"
Delta:,差异值：,sample_size_comp.R
Standard deviation:,标准差,"sample_size_comp.R, sample_size_ui.R"
Power:,效能,sample_size_comp.R
Group 1 less than Group 2,组1 小于 组2,sample_size_comp.R
Group 1 greater than Group 2,组1 大于 组2,sample_size_comp.R
Show plot,显示图形,sample_size_comp.R
Save sample size comparison plot,保存样本量比较图,sample_size_comp.R
Yes,是,sample_size_ui.R
No,否,sample_size_ui.R
"The acceptable error is the level of precision you require (i.e., the range within which the true mean should lie). For example, ± $10. A lower acceptable error requires a larger sample size.",可接受误差是您要求的精度范围（例如，±10美元）。更小的误差要求更大的样本量。,sample_size_ui.R
Acceptable Error:,可接受误差：,sample_size_ui.R
"How much variation is there likely to be in the population? This number is often determined from a previous survey or a pilot study. The higher the standard deviation, the larger the required sample size.",总体可能存在多大的变异？通常通过前期调查或试点研究确定。标准差越大，所需样本量越大。,sample_size_ui.R
What do you expect the sample proportion to be? This number is often determined from a previous survey or a pilot study. If no such information is availabvle use 0.5.,您期望的样本比例是多少？通常通过前期调查或试点研究确定。如无信息请使用0.5。,sample_size_ui.R
"Common values for the confidence level are 0.9, 0.95, and 0.99",置信水平常用值为0.9、0.95 和 0.99,sample_size_ui.R
The probability that a respondent will be part of the target segment of interest,受访者属于目标群体的概率,sample_size_ui.R
Incidence rate:,发生率：,sample_size_ui.R
The probability of a response,响应的概率,sample_size_ui.R
Response rate:,响应率：,sample_size_ui.R
If the sample size is relatively larger compared to the size of the target population you should consider adjusting for population size,如果样本量相对于总体较大，建议调整总体规模,sample_size_ui.R
Correct for population size:,考虑总体规模修正：,sample_size_ui.R
Size of the target population of interest,目标总体的规模,sample_size_ui.R
Population size:,总体规模：,sample_size_ui.R
Sample size (single),样本量（单个）,"sample_size_ui.R,init.R"
"The acceptable error is the level of precision you require (i.e., the range within which the true proportion should lie). For example, ± 0.02. A lower acceptable error requires a larger sample size.",可接受误差是您要求的精度范围（例如，±0.02）。更小的误差要求更大的样本量。,sample_size_ui.R
Proportion 1 (p1):,比例 1（p1）：,sample_size_comp.R
Proportion 2 (p2):,比例 2（p2）：,sample_size_comp.R
No valid sample available,无可用的样本数据,sampling_ui.R
Select at least one variable,请至少选择一个变量,sampling_ui.R
Some selected variables are not available in this dataset,部分选择的变量在数据集中不可用,sampling_ui.R
"For random sampling each row in the data should be distinct(i.e., no duplicates). Please select an appropriate dataset.",为了进行随机抽样，数据中的每一行都应是唯一的（即没有重复项）。请选择一个合适的数据集。\n\n,sampling_ui.R
Please select a sample size of 1 or greater,请选择一个大于等于 1 的样本量,sampling_ui.R
Selected cases,选中的样本,sampling_ui.R
Sampling frame,抽样框架,sampling_ui.R
Sampling,随机抽样,sampling_ui.R
Random sampling,随机抽样,"sampling_ui.R,init.R"
Show sampling frame ,显示抽样框,sampling_ui.R
Proportion,比例,sample_size_ui.R
User id:,用户 ID:,crs_ui.R
Product id:,产品 ID:,crs_ui.R
Choose products to recommend:,选择要推荐的产品:,crs_ui.R
Ratings variable:,评分变量:,crs_ui.R
Estimate model,估计模型,"crs_ui.R, crtree_ui.R, gbt_ui.R, logistic_ui.R,conjoint_ui.R"
Re-estimate model,重新估计模型,"crs_ui.R, crtree_ui.R, gbt_ui.R, logistic_ui.R,conjoint_ui.R"
<label>Store recommendations:</label>,<label>保存推荐结果:</label>,crs_ui.R
Collaborative Filtering,协同过滤,"crs_ui.R,init.R"
Model > Recommend,模型 > 推荐,crs_ui.R
"This analysis requires a user id, a product id, and product ratings.
If these variables are not available please select another dataset.

","此分析需要用户 ID、产品 ID 和评分变量。
如果这些变量不存在，请选择另一个数据集。

",crs_ui.R
"A data filter or slice must be set to generate recommendations using
collaborative filtering. Add a filter or slice in the Data > View tab.
Note that the users in the training sample should not overlap
with the users in the test sample.","必须设置数据过滤或切片才能使用协同过滤生成推荐。
在“数据 > 查看”选项卡中添加过滤器或切片。
注意：训练集和测试集中的用户不应重叠。",crs_ui.R
"An invalid filter has been set for this dataset. Please
adjust the filter in the Data > View tab and try again","此数据集设置了无效的过滤条件。
请在“数据 > 查看”中调整过滤条件并重试。",crs_ui.R
Please select one or more products to generate recommendations,请选择一个或多个产品以生成推荐,crs_ui.R
Estimating model,正在估计模型,"crs_ui.R, crtree_ui.R,conjoint_ui.R"
** Press the Estimate button to generate recommendations **,** 请点击“估计模型”按钮以生成推荐 **,crs_ui.R
No data selected to generate recommendations,未选择任何数据用于生成推荐,crs_ui.R
Dataset '{fixed}' was successfully added to the datasets dropdown. Add code to Report > Rmd or Report > R to (re)create the dataset by clicking the report icon on the bottom left of your screen.,数据集“{fixed}”已成功添加到数据下拉菜单中。要在报告中（重新）生成该数据集，请点击左下角的报告图标，并添加到“报告 > Rmd”或“报告 > R”。,crs_ui.R
No recommendations available,无推荐结果可用,crs_ui.R
Save collaborative filtering recommendations,保存协同过滤推荐结果,crs_ui.R
Save collaborative filtering plot,保存协同过滤图表,crs_ui.R
Prune,修剪,crtree_ui.R
Tree,决策树,crtree_ui.R
Permutation Importance,特征重要性,"crtree_ui.R, gbt_ui.R"
Prediction plots,预测图,"crtree_ui.R, gbt_ui.R"
Partial Dependence,部分依赖图,"crtree_ui.R, gbt_ui.R"
Dashboard,仪表盘,"crtree_ui.R, gbt_ui.R"
Response variable:,因变量:,"crtree_ui.R, evalbin_ui.R, evalreg_ui.R, gbt_ui.R, logistic_ui.R"
Explanatory variables:,自变量:,"crtree_ui.R, gbt_ui.R, logistic_ui.R"
Explanatory variables to include:,包含的自变量:,"crtree_ui.R, logistic_ui.R"
2-way interactions to explore:,要探索的二阶交互项:,"crtree_ui.R, logistic_ui.R"
Weights:,权重:,"crtree_ui.R, gbt_ui.R, logistic_ui.R"
classification,分类,"crtree_ui.R, gbt_ui.R"
regression,回归,"crtree_ui.R, gbt_ui.R"
Prior:,先验:,crtree_ui.R
Min obs.:,最小观测数:,crtree_ui.R
Cost:,成本:,"crtree_ui.R, evalbin_ui.R"
Margin:,边际:,"crtree_ui.R, evalbin_ui.R"
Complexity:,复杂度:,crtree_ui.R
Max. nodes:,最大节点数:,crtree_ui.R
Prune compl.:,修剪复杂度:,crtree_ui.R
Store residuals:,存储残差:,"crtree_ui.R, logistic_ui.R"
Provide variable name,输入变量名称,"crtree_ui.R,hclus_ui.R"
Classification and regression trees,分类与回归树,"crtree_ui.R,init.R"
Prediction input type:,预测输入类型:,"crtree_ui.R, gbt_ui.R, logistic_ui.R,conjoint_ui.R"
Prediction data:,预测数据:,"crtree_ui.R, gbt_ui.R,conjoint_ui.R"
Prediction command:,预测指令:,"crtree_ui.R, gbt_ui.R, logistic_ui.R,conjoint_ui.R"
"Type a formula to set values for model variables (e.g., carat = 1; cut = 'Ideal') and press return",在此输入用于模型预测的变量值 (如 carat = 1; cut = 'Ideal') 并按回车键,"crtree_ui.R, gbt_ui.R, naivebayes_ui.R"
Plot predictions,绘制预测图,"crtree_ui.R, gbt_ui.R, logistic_ui.R,conjoint_ui.R"
Store predictions:,存储预测值:,"crtree_ui.R, gbt_ui.R,conjoint_ui.R"
Plots:,绘图选项:,"crtree_ui.R, evalbin_ui.R, gbt_ui.R, logistic_ui.R"
Plot direction:,绘图方向:,"crtree_ui.R, dtree_ui.R"
Left-right,左-右,"crtree_ui.R, dtree_ui.R"
Top-down,上-下,"crtree_ui.R, dtree-ui.R"
Right-left,右-左,crtree_ui.R
Bottom-Top,下-上,crtree_ui.R
Width:,宽度:,crtree_ui.R
Save crtree predictions,保存预测结果,crtree_ui.R
Save decision tree prediction plot,保存预测图,crtree_ui.R
Save decision tree plot,保存决策树图,crtree_ui.R
Generating predictions,正在生成预测,"crtree_ui.R, gbt_ui.R, logistic_ui.R,conjoint_ui.R"
Generating prediction plot,正在生成预测图,"crtree_ui.R, gbt_ui.R, logistic_ui.R,conjoint_ui.R"
Generating tree diagramm,正在生成树图,crtree_ui.R
Model > Estimate,模型 > 估计,"crtree_ui.R, logistic_ui.R"
** Press the Estimate button to estimate the model **,** 点击“估计模型”按钮来估计模型 **,"crtree_ui.R, gbt_ui.R,conjoint_ui.R"
Please select one or more explanatory variables.,请选择一个或多个自变量。,"crtree_ui.R, gbt_ui.R, nn_ui.R"
Max,最大化,dtree_ui.R
Min,最小化,dtree_ui.R
Remove,删除,dtree_ui.R
"No variables are available for sensitivity analysis. If the input file does contain a variables section, press the Calculate button to show the list of available variables.",没有可用于敏感性分析的变量。如果输入文件包含 variables 部分，请点击“计算树”按钮以显示可用变量列表。,dtree_ui.R
Sensitivity to changes in:,敏感性分析变量：,dtree_ui.R
Decisions to evaluate:,要评估的决策：,dtree_ui.R
Select decisions to evaluate,选择要评估的决策,dtree_ui.R
"<label>Add variable: <i id='dtree_sense_add' title='Add variable' href='#' class='action-button fa fa-plus-circle'></i>
          <i id='dtree_sense_del' title='Remove variable' href='#' class='action-button fa fa-minus-circle'></i></label>","<label>添加变量: <i id='dtree_sense_add' title='添加变量' href='#' class='action-button fa fa-plus-circle'></i>
          <i id='dtree_sense_del' title='删除变量' href='#' class='action-button fa fa-minus-circle'></i></label>",dtree_ui.R
Step:,步长:,dtree_ui.R
Model,模型,"dtree_ui.R,init.R"
Decision analysis,决策分析,"dtree_ui.R,init.R"
<i title='Report results' class='fa fa-edit action-button' href='#dtree_report1' id='dtree_report1'></i>,<i title='报告结果' class='fa fa-edit action-button' href='#dtree_report1' id='dtree_report1'></i>,dtree_ui.R
<i title='Report results & Screenshot' class='fa fa-camera action-button aligncenter' href='#dtree_screenshot1' id='dtree_screenshot1' onclick='generate_screenshot();'></i>,<i title='报告结果并截图' class='fa fa-camera action-button aligncenter' href='#dtree_screenshot1' id='dtree_screenshot1' onclick='generate_screenshot();'></i>,dtree_ui.R
Calculate tree,计算树,dtree_ui.R
Load input,加载输入,dtree_ui.R
Load decision tree input file (.yaml),加载决策树输入文件 (.yaml),dtree_ui.R
Save input,保存输入,dtree_ui.R
Save output,保存输出,dtree_ui.R
Provide structured input for a decision tree. Then click the 'Calculate tree' button to generate results. Click the ? icon on the top left of your screen for help and examples,为决策树提供结构化输入，然后点击“计算树”按钮生成结果。如需帮助和示例，请点击左上角的 ? 图标。,dtree_ui.R
<i title='Save plot' class='fa fa-download action-button alignright' href='#dtree_screenshot3' id='dtree_screenshot3' onclick='generate_dtree_plot();'></i>,<i title='保存图形' class='fa fa-download action-button alignright' href='#dtree_screenshot3' id='dtree_screenshot3' onclick='generate_dtree_plot();'></i>,dtree_ui.R
<i title='Report results' class='fa fa-edit action-button' href='' id='dtree_report2'></i>,<i title='报告结果' class='fa fa-edit action-button' href='' id='dtree_report2'></i>,dtree_ui.R
<i title='Report results & Screenshot' class='fa fa-camera action-button aligncenter' href='#dtree_screenshot2' id='dtree_screenshot2' onclick='generate_screenshot();'></i>,<i title='报告结果并截图' class='fa fa-camera action-button aligncenter' href='#dtree_screenshot2' id='dtree_screenshot2' onclick='generate_screenshot();'></i>,dtree_ui.R
Plot decision tree:,绘制决策树：,dtree_ui.R
Initial,初始,dtree_ui.R
Final,最终,dtree_ui.R
Decimals,小数位,dtree_ui.R
Symbol,符号,dtree_ui.R
Sensitivity,敏感性,dtree_ui.R
Evaluate sensitivity,评估敏感性,dtree_ui.R
At least one decision should be selected for evaluation,至少应选择一个决策进行评估,dtree_ui.R
No variables were specified for evaluation.\nClick the + icon to add variables for sensitivity evaluation,未指定任何变量用于评估。\n点击 + 图标添加要进行敏感性评估的变量,dtree_ui.R
Conducting sensitivity analysis,正在进行敏感性分析,dtree_ui.R
Creating decision tree,正在创建决策树,dtree_ui.R
** Click the calculate button to generate results **,** 请点击计算按钮以生成结果 **,dtree_ui.R
Save decision tree output,保存决策树输出,dtree_ui.R
Save decision tree input,保存决策树输入,dtree_ui.R
Save decision tree sensitivity plot,保存敏感性分析图,dtree_ui.R
Lift,提升图,evalbin_ui.R
Gains,收益图,evalbin_ui.R
Profit,利润图,evalbin_ui.R
Expected profit,预期利润,evalbin_ui.R
ROME,投资回报率,evalbin_ui.R
Training,训练集,"evalbin_ui.R, evalreg_ui.R"
Test,测试集,"evalbin_ui.R, evalreg_ui.R"
Both,训练集与测试集,"evalbin_ui.R, evalreg_ui.R"
Incremental uplift,增量提升,evalbin_ui.R
Uplift,提升,evalbin_ui.R
Incremental profit,增量利润,evalbin_ui.R
More than 50 levels. Please choose another response variable,超过 50 个水平。请选择其他响应变量,evalbin_ui.R
Treatment variable:,处理变量：,evalbin_ui.R
Select stored predictions:,选择已保存的预测：,"evalbin_ui.R, evalreg_ui.R"
Show results for:,显示结果：,"evalbin_ui.R, evalreg_ui.R"
Store uplift table as:,保存提升表为：,evalbin_ui.R
Evaluate models,评估模型,"evalbin_ui.R, evalreg_ui.R"
Re-evaluate models,重新评估模型,"evalbin_ui.R, evalreg_ui.R"
# quantiles:,分位数数量：,evalbin_ui.R
Scale:,缩放因子：,evalbin_ui.R
Show model performance table,显示模型性能表,evalbin_ui.R
Show uplift table,显示提升表,evalbin_ui.R
Show plots,显示图形,"evalbin_ui.R, evalreg_ui.R"
Scale free,统一纵轴,evalbin_ui.R
Evaluate classification,分类模型评估,"evalbin_ui.R,init.R"
Confusion matrix,混淆矩阵,evalbin_ui.R
Evaluate uplift,评估提升效果,evalbin_ui.R
Uplift Table Stored,提升表已保存,evalbin_ui.R
The uplift table ',提升表 ',evalbin_ui.R
"' was successfully added to the
                datasets dropdown. Add code to Report > Rmd or
                Report > R to (re)create the results by clicking
                the report icon on the bottom left of your screen.",' 已成功添加到数据集下拉菜单。可在 Report > Rmd 或 Report > R 中添加代码以（重新）生成结果，方法是点击屏幕左下角的报告图标。,evalbin_ui.R
Save model evaluations,保存模型评估结果,"evalbin_ui.R, evalreg_ui.R"
Save model performance metrics,保存模型性能指标,evalbin_ui.R
Save uplift evaluations,保存提升评估结果,evalbin_ui.R
Save model evaluation plot,保存模型评估图,"evalbin_ui.R, evalreg_ui.R"
Save confusion plots,保存混淆图,evalbin_ui.R
Save uplift plots,保存提升图,evalbin_ui.R
Evaluate,评估,"evalbin_ui.R,init.R"
Model > Evaluate,模型 > 评估,"evalbin_ui.R, evalreg_ui.R"
** Press the Evaluate button to evaluate models **,** 请点击“评估”按钮以评估模型 **,"evalbin_ui.R, evalreg_ui.R"
<label>More than 50 levels. Please choose another response variable</label>,<label>超过 50 个水平。请选择其他响应变量</label>,evalbin_ui.R
"This analysis requires a response variable of type factor and one or more
predictors of type numeric. If these variable types are not available please
select another dataset.

For an example dataset go to Data > Manage, select 'examples' from the
'Load data of type' dropdown, and press the 'Load examples' button. Then
select the 'titanic' dataset.","此分析需要一个因变量（类别型）和一个或多个自变量（数值型）。如果这些变量类型不可用，请选择另一个数据集。

如需示例数据集，请前往“数据 > 管理”，在“加载数据类型”下拉菜单中选择“示例”，然后点击“加载示例”按钮。接着选择“titanic”数据集。",evalbin_ui.R
"This analysis requires a response variable of type factor and one or more
predictors of type numeric. If these variable types are not available please
select another dataset.
",此分析需要一个因变量（类别型）和一个或多个自变量（数值型）。如果这些变量类型不可用，请选择另一个数据集。,evalbin_ui.R
Evaluate Regression,回归模型评估,evalreg_ui.R
This analysis requires a numeric response variable and one or more\nnumeric predictors. If these variable types are not available please\nselect another dataset.\n\n,本分析要求一个数值型因变量和一个或多个数值型自变量。如果当前数据集中不包含这些类型的变量，请选择另一个数据集。\n\n,evalreg_ui.R
Choose first level:,选择第一个水平：,gbt_ui.R
Max depth:,最大深度：,gbt_ui.R
Learning rate:,学习率：,gbt_ui.R
Min split loss:,最小分裂损失：,gbt_ui.R
Min child weight:,最小子节点权重：,gbt_ui.R
Sub-sample:,子样本比例：,gbt_ui.R
# rounds:,迭代轮数：,gbt_ui.R
Early stopping:,提前停止：,gbt_ui.R
Gradient Boosted Trees,梯度提升树,"gbt_ui.R,init.R"
Model > Trees,模型 > 树模型,gbt_ui.R
** Select prediction input **,** 请选择预测输入 **,"gbt_ui.R, logistic_ui.R,conjoint_ui.R"
** Select data for prediction **,** 请选择用于预测的数据 **,"gbt_ui.R, logistic_ui.R,conjoint_ui.R"
** Enter prediction commands **,** 请输入预测命令 **,"gbt_ui.R, logistic_ui.R,conjoint_ui.R"
Please select a gradient boosted trees plot from the drop-down menu,请从下拉菜单中选择一个梯度提升树图表,gbt_ui.R
Storing predictions,正在保存预测结果,"gbt_ui.R, logistic_ui.R,conjoint_ui.R"
No output available. Press the Estimate button to generate results,无可用输出。请点击“估计模型”按钮生成结果,"gbt_ui.R, logistic_ui.R,conjoint_ui.R"
Save predictions,保存预测结果,"gbt_ui.R, logistic_ui.R,conjoint_ui.R"
Save gradient boosted trees prediction plot,保存梯度提升树预测图,gbt_ui.R
Save gradient boosted trees plot,保存梯度提升树图,gbt_ui.R
This analysis requires a response variable with two levels and one\nor more explanatory variables. If these variables are not available\nplease select another dataset.\n\n,此分析需要一个具有两个水平的响应变量和一个\n或多个解释变量。如果这些变量不可用\n请选择其他数据集。\n\n,gbt_ui.R
This analysis requires a response variable of type integer\nor numeric and one or more explanatory variables.\nIf these variables are not available please select another dataset.\n\n,此分析需要一个整数类型的响应变量\n或数值型，以及一个或多个解释变量。\n如果这些变量不可用，请选择其他数据集。\n\n,gbt_ui.R
Predict,预测,"gbt_ui.R,conjoint_ui.R"
Storing residuals,存储残差,logistic_ui.R
Save coefficients,保存系数,logistic_ui.R
Save logistic prediction plot,保存逻辑回归预测图,logistic_ui.R
Save logistic plot,保存逻辑回归图,logistic_ui.R
Variables to test:,测试的变量：,logistic_ui.R
"Type a formula to set values for model variables (e.g., class = '1st'; gender = 'male') and press return",输入公式设置模型变量的值（例如，class = '1st'; gender = 'male'），然后按回车,logistic_ui.R
Include intercept,包含截距,logistic_ui.R
Logistic regression (GLM),逻辑回归（广义线性模型）,"logistic_ui.R,init.R"
Logistic regression,逻辑回归,logistic_ui.R
3-way,三因素交互,"logistic_ui.R,conjoint_ui.R"
Data,数据,"logistic_ui.R,conjoint_ui.R,global.R"
Command,命令,"logistic_ui.R,conjoint_ui.R"
Data & Command,数据和命令,"logistic_ui.R,conjoint_ui.R"
Stepwise, "逐步回归", "logistic_ui.R"
Robust, "稳健", "logistic_ui.R"
VIF,方差膨胀因子,"logistic_ui.R,conjoint_ui.R"
Confidence intervals, "置信区间", "logistic_ui.R"
Odds, "赔率", "logistic_ui.R"
Correlations, "相关性", "logistic_ui.R"
Model fit, "模型拟合", "logistic_ui.R"
Coefficient (OR) plot, "系数（OR）图", "logistic_ui.R"
Influential observations, "影响观察值", "logistic_ui.R"
This analysis requires a response variable with two levels and one or more explanatory variables. If these variables are not available please select another dataset.,该分析需要一个具有两个级别的响应变量以及一个或多个解释变量。如果这些变量不可用，请选择另一个数据集。, "logistic_ui.R"
Drop intercept,去除截距项,mnl_ui.R
RRRs,相对风险比 (RRR),mnl_ui.R
Coefficient (RRR) plot,系数图（RRR）,mnl_ui.R
Multinomial logistic regression (MNL),多项式逻辑回归（MNL）,"mnl_ui.R,init.R"
Save mnl prediction plot,保存 MNL 预测图,mnl_ui.R
Save mnl plot,保存 MNL 图表,mnl_ui.R
Please select a mnl regression plot from the drop-down menu,请从下拉菜单中选择一个 MNL 回归图,mnl_ui.R
Choose base level:,选择基准水平：,mnl_ui.R
Variable importance,变量重要性,naivebayes_ui.R
Naive Bayes,朴素贝叶斯,"naivebayes_ui.R,init.R"
Laplace:,拉普拉斯修正：,naivebayes_ui.R
Save naive Bayes prediction plot,保存朴素贝叶斯预测图,naivebayes_ui.R
Save naive Bayes plot,保存朴素贝叶斯图,naivebayes_ui.R
Please select a naive Bayes plot from the drop-down menu,请从下拉菜单中选择一个朴素贝叶斯图,naivebayes_ui.R
All levels,所有水平,naivebayes_ui.R
Network,网络结构,nn_ui.R
Olden,节点权重贡献图（Olden 方法）,nn_ui.R
Garson,输入变量重要性图（Garson 方法）,nn_ui.R
Neural Network,神经网络,"nn_ui.R,init.R"
Regression,回归,nn_ui.R
Decay:,衰减：,nn_ui.R
Save neural network prediction plot,保存神经网络预测图,nn_ui.R
Save neural network plot,保存神经网络图,nn_ui.R
Please select a neural network plot from the drop-down menu,请从下拉菜单中选择一种神经网络图,nn_ui.R
RMSE,均方根误差,regress_ui.R
Sum of squares,平方和,regress_ui.R
Residual vs explanatory,残差对解释变量图,regress_ui.R
Coefficient plot,系数图,regress_ui.R
Linear regression (OLS),线性回归（普通最小二乘法）,"regress_ui.R,init.R"
Save regression predictions,保存回归预测结果,regress_ui.R
Save regression plot,保存回归图表,regress_ui.R
Please select one or more explanatory variables. Then press the Estimate\nbutton to estimate the model.,请选择一个或多个解释变量，然后点击“估计模型”按钮。,regress_ui.R
Save regression prediction plot,保存回归预测图,regress_ui.R
Please select a regression plot from the drop-down menu,请从下拉菜单中选择一个回归图,regress_ui.R
Random Forest,随机森林,"rforest_ui.R,init.R"
mtry:,mtry：特征子集数,rforest_ui.R
# trees:,树数量：,rforest_ui.R
Min node size:,最小节点样本数：,rforest_ui.R
Sample fraction:,样本抽样比例：,rforest_ui.R
Save random forest plot,保存随机森林图,rforest_ui.R
Constant,常数,simulater_ui.R
Grid search,网格搜索,simulater_ui.R
Sequence,序列,simulater_ui.R
Repeat simulation,重复模拟,simulater_ui.R
<label>Simulation formulas:</label>,<label>模拟公式：</label>,simulater_ui.R
"Use formulas to perform calculations on simulated variables
(e.g., demand = 5 * price). Press the Run simulation button
to run the simulation. Click the ? icon on the bottom left
of your screen for help and examples",使用公式对模拟变量进行计算（例如：demand = 5 * price）。点击“运行模拟”按钮开始模拟。点击左下角的问号图标查看帮助和示例。,simulater_ui.R
</br><label>Simulation functions:</label>,</br><label>模拟函数：</label>,simulater_ui.R
"Create your own R functions (e.g., add = function(x, y) {x + y}).
Call these functions from the 'formula' input and press the Run
simulation button to run the simulation. Click the ? icon on the
bottom left of your screen for help and examples","创建你自己的 R 函数（例如：add = function(x, y) {x + y}）。在“公式”输入框中调用这些函数并点击“运行模拟”按钮。点击左下角的问号图标查看帮助和示例。",simulater_ui.R
Repeat,重复,simulater_ui.R
<label>Repeated simulation formulas:</label>,<label>重复模拟公式：</label>,simulater_ui.R
"Press the Repeat simulation button to repeat the simulation specified in the
Simulate tab. Use formulas to perform additional calculations on the repeated
simulation data. Click the ? icon on the bottom left of your screen for help
and examples",点击“重复模拟”按钮，对“模拟”页中指定的模拟进行重复执行。你可以使用公式对重复模拟的数据执行额外计算。点击左下角的问号图标查看帮助和示例。,simulater_ui.R
</br><label>Repeated simulation functions:</label>,</br><label>重复模拟函数：</label>,simulater_ui.R
</br><label>Repeated simulation summary:</label>,</br><label>重复模拟汇总：</label>,simulater_ui.R
</br><label>Repeated simulation plots:</label>,</br><label>重复模拟图表：</label>,simulater_ui.R
Model > Decide,建模 > 决策,simulater_ui.R
Name:,名称：,simulater_ui.R
Prob.:,概率：,simulater_ui.R
St.dev.:,标准差：,simulater_ui.R
Use exact specifications,使用精确指定,simulater_ui.R
Correlations:,相关性：,simulater_ui.R
Set random seed:,设置随机种子：,"simulater_ui.R,kclus_ui.R"
# sims:,模拟次数：,simulater_ui.R
Simulated data:,模拟数据：,simulater_ui.R
Add functions,添加函数,simulater_ui.R
Select types,选择类型,simulater_ui.R
Select types:,选择类型：,simulater_ui.R
Save simulation plots,保存模拟图表,simulater_ui.R
** Press the Repeat simulation button **,** 请点击“重复模拟”按钮 **,simulater_ui.R
sum,求和,simulater_ui.R
mean,均值,simulater_ui.R
median,中位数,simulater_ui.R
min,最小值,simulater_ui.R
max,最大值,simulater_ui.R
sd,标准差,simulater_ui.R
var,方差,simulater_ui.R
sdprop,标准差比例,simulater_ui.R
varprop,方差比例,simulater_ui.R
p01,第1百分位数,simulater_ui.R
p025,第2.5百分位数,simulater_ui.R
p05,第5百分位数,simulater_ui.R
p10,第10百分位数,simulater_ui.R
p25,第25百分位数,simulater_ui.R
p75,第75百分位数,simulater_ui.R
p90,第90百分位数,simulater_ui.R
p95,第95百分位数,simulater_ui.R
p975,第97.5百分位数,simulater_ui.R
p99,第99百分位数,simulater_ui.R
first,第一个值,simulater_ui.R
last,最后一个值,simulater_ui.R
Provide values in the input boxes above and then press the + symbol,请在上方输入框中填写数值，然后点击加号按钮,simulater_ui.R
# reps:,重复次数：,simulater_ui.R
Repeat data:,重复模拟数据：,simulater_ui.R
No formulas or simulated variables specified,未指定任何公式或模拟变量,simulater_ui.R
Running simulation,正在运行模拟,simulater_ui.R
Generating simulation plots,正在生成模拟图表,simulater_ui.R
</br><label>Simulation summary:</label>,</br><label>模拟摘要：</label>,simulater_ui.R
</br><label>Simulation plots:</label>,</br><label>模拟图表：</label>,simulater_ui.R
Simulation,模拟,simulater_ui.R
Binomial variables:, "二项变量：", "simulater_ui.R"
Grid search:, "网格搜索：", "simulater_ui.R"
Save repeated simulation plots, "保存重复模拟图", "simulater_ui.R"
Inputs required, "需要输入", "simulater_ui.R"
Select at least one Output variable, "请至少选择一个输出变量", "simulater_ui.R"
Constant variables,常量变量,simulater_ui.R
Discrete variables,离散变量,simulater_ui.R
Log-normal variables,对数正态变量,simulater_ui.R
Normal variables,正态变量,simulater_ui.R
Poisson variables,泊松变量,simulater_ui.R
Uniform variables,均匀变量,simulater_ui.R
Sequence variables,序列变量,simulater_ui.R
2-way,双因素交互,conjoint_ui.R
Part-worths,部分效用,conjoint_ui.R
Importance-weights,重要性权重,conjoint_ui.R
Profile evaluations:,方案评价:,conjoint_ui.R
Attributes:,属性:,conjoint_ui.R
By:,按:,conjoint_ui.R
Show:,显示:,conjoint_ui.R
Store all PWs in a new dataset:,将所有部分效用存入新数据集:,conjoint_ui.R
Store all IWs in a new dataset:,将所有重要性权重存入新数据集:,conjoint_ui.R
in new dataset:,到新数据集中:,conjoint_ui.R
Reverse evaluation scores,反转评分,conjoint_ui.R
Additional regression output,附加回归输出,conjoint_ui.R
Conjoint plots:,联合分析图:,conjoint_ui.R
Scale PW plots,缩放部分效用图,conjoint_ui.R
Conjoint,联合分析,"conjoint_ui.R,init.R"
** Press the Estimate button to run the conjoint analysis **,** 点击“估计模型”按钮运行联合分析 **,conjoint_ui.R
"This analysis requires a response variable of type integer\nor numeric and one or more explanatory variables.
If these variables are not available please select another dataset.",此分析需要一个整数或数值型的响应变量以及一个或多个解释变量。\n如果这些变量不可用，请选择其他数据集。\n\n,conjoint_ui.R
"Please select one or more explanatory variables of type factor.
If none are available please choose another dataset",请选择一个或多个因子型解释变量。\n如果没有可用变量，请选择其他数据集\n\n,conjoint_ui.R
Please select a conjoint plot from the drop-down menu,请从下拉菜单中选择一个联合分析图,conjoint_ui.R
Storing PWs,正在存储部分效用,conjoint_ui.R
Storing IWs,正在存储重要性权重,conjoint_ui.R
Storing predictions in new dataset,正在将预测结果存储到新数据集,conjoint_ui.R
Save part worths,保存部分效用,conjoint_ui.R
Save conjoint prediction plot,保存联合分析预测图,conjoint_ui.R
Save conjoint plot,保存联合分析图,conjoint_ui.R
Multivariate > Conjoint,多元分析 > 联合分析,conjoint_ui.R
Principal components,主成分,full_factor_ui.R
Maximum Likelihood,极大似然,full_factor_ui.R
Varimax,方差最大旋转,full_factor_ui.R
Quartimax,四次最大旋转,full_factor_ui.R
Equamax,均方最大旋转,full_factor_ui.R
Promax,Promax 旋转,full_factor_ui.R
Oblimin,Oblimin 旋转,full_factor_ui.R
Simplimax,简单最大旋转,full_factor_ui.R
Multivariate > Factor,多元分析 > 因子分析,full_factor_ui.R
Factor,因子分析,"full_factor_ui.R,init.R"
Respondents,受访者,full_factor_ui.R
Nr. of factors:,因子数量：,full_factor_ui.R
Cutt-off:,截断值：,full_factor_ui.R
Sort factor loadings,对因子载荷排序,full_factor_ui.R
rotation:,旋转：,full_factor_ui.R
Save factor loadings,保存因子载荷,full_factor_ui.R
** Press the Estimate button to generate factor analysis results **,** 请点击“估计模型”按钮以生成因子分析结果 **,full_factor_ui.R
Store factor scores:,存储因子得分：,full_factor_ui.R
Provide single variable name,请输入单个变量名,full_factor_ui.R
Save factor plots,保存因子图,full_factor_ui.R
Please select two or more variables,请选择两个或以上变量,full_factor_ui.R
Provide a correlation cutoff value in the range from 0 to 1,请输入 0 到 1 范围内的相关性截断值,full_factor_ui.R
Estimating factor solution,正在估计因子解,full_factor_ui.R
Generating factor plots,正在生成因子图,full_factor_ui.R
Ward's,沃德法,hclus_ui.R
Single,单连接,hclus_ui.R
Complete,全连接,hclus_ui.R
Average,平均连接,hclus_ui.R
McQuitty,麦奎蒂法,hclus_ui.R
Median,中位数法,hclus_ui.R
Centroid,质心法,hclus_ui.R
Squared euclidean,平方欧几里得,hclus_ui.R
Binary,二元距离,hclus_ui.R
Canberra,堪培拉距离,hclus_ui.R
Euclidian,欧几里得距离,hclus_ui.R
Gower,高尔距离,hclus_ui.R
Manhattan,曼哈顿距离,hclus_ui.R
Maximum,最大距离,hclus_ui.R
Minkowski,闵可夫斯基距离,hclus_ui.R
Scree,碎石图,hclus_ui.R
Change,变化图,hclus_ui.R
Dendrogram,树状图,hclus_ui.R
Multivariate > Cluster,多元分析 > 聚类,hclus_ui.R
Hierarchical,层次聚类,"hclus_ui.R,init.R"
Distance measure:,距离度量:,hclus_ui.R
Select plot(s),选择图表,hclus_ui.R
Plot(s):,图表:,hclus_ui.R
Plot cutoff:,图表截断值:,hclus_ui.R
Max cases:,最大案例数:,hclus_ui.R
Number of clusters:,聚类数:,hclus_ui.R
Store cluster membership:,保存聚类成员:,hclus_ui.R
Hierarchical cluster analysis,层次聚类分析,hclus_ui.R
Save hierarchical cluster plots,保存层次聚类图,hclus_ui.R
"This analysis requires one or more variables of type integer or numeric.
If these variable types are not available please select another dataset.","此分析需要一个或多个整数或数值型变量。如果这些变量类型不可用，请选择其他数据集。
",hclus_ui.R
Generating cluster plot,正在生成聚类图,hclus_ui.R
Labels:,标签:,hclus_ui.R
** Press the Estimate button to generate cluster solution **,** 点击“估计模型”按钮以生成聚类结果 **,hclus_ui.R
Estimating cluster solution,正在计算聚类结果,hclus_ui.R
K-means,K-均值,kclus_ui.R
K-proto,K-原型,kclus_ui.R
K-clustering,K均值聚类,"kclus_ui.R,init.R"
Algorithm:,算法：,kclus_ui.R
Initial centers from HC,使用层次聚类初始化中心,kclus_ui.R
Save clustering results ,保存聚类结果 ,kclus_ui.R
** Press the Estimate button to generate the cluster solution **,** 请点击“估计模型”按钮以生成聚类结果 **,kclus_ui.R
"This analysis requires one or more variables of type numeric or integer.
If these variable types are not available please select another dataset.",此分析需要一个或多个数值型或整数型变量。\n如果这些变量类型不可用，请选择其他数据集。,kclus_ui.R
Save k-cluster plots,保存 K-聚类图,kclus_ui.R
Please select a plot type from the drop-down menu,请从下拉菜单中选择图表类型,kclus_ui.R
"This analysis requires multiple variables of type numeric or integer.
If these variables are not available please select another dataset.",该分析需要多个数值型或整数型变量。\n如果这些变量不可用，请选择其他数据集。,full_factor_ui.R
"Plot requires 2 or more factors.
Change the number of factors in the Summary tab and re-estimate",绘图需要 2 个或更多因子。\n请在“摘要”选项卡中更改因子数量并重新估计,full_factor_ui.R
2 dimensions,二维,mds_ui.R
3 dimensions,三维,mds_ui.R
metric,度量型,mds_ui.R
non-metric,非度量型,mds_ui.R
Multivariate > Maps,多元分析 > 映射,mds_ui.R
(Dis)similarity,(不)相似性分析,"mds_ui.R,init.R"
Font size:,字体大小：,mds_ui.R
(Dis)similarity based brand maps (MDS),基于（不）相似性的感知图（MDS）,mds_ui.R
Save MDS coordinates,保存 MDS 坐标,mds_ui.R
** Press the Estimate button to generate maps **,** 请点击“估计模型”按钮以生成地图 **,mds_ui.R
ID 1:,ID 1：,mds_ui.R
ID 2:,ID 2：,mds_ui.R
Dissimilarity:,相异度：,mds_ui.R
Generating MDS solution,正在生成 MDS 解,mds_ui.R
Save MDS plot,保存 MDS 图,mds_ui.R
Reverse:,反向：,mds_ui.R
Pre-factor,预因子分析,"pre_factor_ui.R,init.R"
Pre-factor analysis,预因子分析,pre_factor_ui.R
** Press the Estimate button to generate factor analysis diagnostics **,** 请点击“估计模型”按钮以生成因子分析诊断 **,pre_factor_ui.R
Save pre-factor plot,保存预因子图,pre_factor_ui.R
Please select two or more numeric variables,请选择两个或更多数值变量,pre_factor_ui.R
Loadings cutoff:,因子载荷阈值：,prmap_ui.R
Attribute scale:,指标刻度：,prmap_ui.R
Attribute based brand maps,基于指标的机构感知图,prmap_ui.R
** Press the Estimate button to generate perceptual maps **,** 点击“估计模型”按钮生成感知图 **,prmap_ui.R
Brand:,机构变量：,prmap_ui.R
"This analysis requires a brand variable of type factor or character and multiple attribute variables
of type numeric or integer. If these variables are not available please select another dataset.",本分析需要一个因子型或字符型的机构变量，以及多个数值型或整型的指标变量。\n如果数据集中不包含这些变量，请选择其他数据集。\n\n,prmap_ui.R
Save preceptual map plot,保存感知图,prmap_ui.R
Brands,机构,prmap_ui.R
Preferences:,偏好：,prmap_ui.R
Preferences,偏好,prmap_ui.R
Please select two or more attribute variables,请选择两个或更多属性变量,prmap_ui.R
Generating perceptual map,正在生成感知地图,prmap_ui.R
Generating brand maps,正在生成机构地图,prmap_ui.R
Share radiant state,分享Radiant状态,global.R
View radiant state,查看Radiant状态,global.R
Download radiant state file,下载Radiant状态文件,global.R
Upload radiant state file,上传Radiant状态文件,global.R
Stop,停止,global.R
Refresh,刷新,global.R
New session,新建会话,global.R
Videos,视频,global.R
About,关于,global.R
Radiant docs,Radiant文档,global.R
Report issue,报告问题,global.R
Design,设计,init.R
Sample,样本,init.R
Basics,基础,init.R
Probability,概率,init.R
Means,均值,init.R
Proportions,比例,init.R
Tables,表格,init.R
Estimate,估计,init.R
Trees,树模型,init.R
Evaluate regression,回归模型评估,init.R
Recommend,推荐,init.R
Decide,决策,init.R
Multivariate,多元分析,init.R
Maps,感知图,init.R
Attributes,属性分析,init.R
Cluster,聚类分析,init.R
Report,报告,"global.R,radiant.R"
Evaluate regressions,回归模型评估,evalreg_ui.R
Knit report (Rmd),编译报告 (Rmd),"report_rmd.R,report_r.R"
Knit report (R),编译报告 (R),"report_rmd.R,report_r.R"
Save report,保存报告,"report_rmd.R,report_r.R"
Load report,加载报告,"report_rmd.R,report_r.R"
Read files,读取文件,"report_rmd.R,report_r.R"
Clear output,清除输出,"report_rmd.R,report_r.R"
General,一般指令,help.R
Save state,保存状态文件,help.R
Open state,打开状态文件,help.R
Show help,显示帮助,help.R
Generate screenshot,生成截图,help.R
Generate code,生成代码,help.R
Estimate/Run (green button),估算/运行（绿色按钮）,help.R
Save (blue button),保存（蓝色按钮）,help.R
Download (blue icon),下载（蓝色图标）,help.R
Load (blue button),加载（蓝色按钮）,help.R
Radiant for R,医学科研统计工具,"global.R,ui.R"
Base dir:,根目录：,global.R
Generate descriptive statistics with one click,一键生成描述性统计,"quickgen_basic_ui.R,init.R"
Oneclick generation > Generate descriptive statistics,一键生成 > 生成描述性统计,quickgen_basic_ui.R
Oneclick generation,一键生成,init.R
LLM generates descriptive statistics,大模型生成描述性统计,init.R
Select All,全选,quickgen_basic_ui.R
Deselect All,全不选,quickgen_basic_ui.R
Invert,反选,quickgen_basic_ui.R
Radiant screenshot,截图,radiant.R
Cancel,取消,radiant.R
Table,表格,quickgen_basic_ui.R
OneClick table generation,一键成表,quickgen_basic_ui.R
Select numeric variables,选择数值变量,quickgen_basic_ui.R
Chart,图表,quickgen_basic_ui.R
OneClick chart generation,一键生图,quickgen_basic_ui.R
Select Y variable(s),选择Y变量,quickgen_basic_ui.R
Select X variable(s),选择X变量,quickgen_basic_ui.R
No data available,暂无数据,quickgen_basic_ui.R
No numerical variable available,无可用数值变量,quickgen_basic_ui.R
### Current data overview,### 当前数据概况,quickgen_basic_ui.R