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chore: 修改自动机器学习特征预处理算法中文描述

pull/269/head
zhaowei 7 months ago
parent
commit
af78389c11
1 changed files with 23 additions and 17 deletions
  1. +23
    -17
      react-ui/src/pages/AutoML/components/CreateForm/utils.ts

+ 23
- 17
react-ui/src/pages/AutoML/components/CreateForm/utils.ts View File

@@ -42,37 +42,43 @@ export const regressorAlgorithms = [


// 特征预处理算法 // 特征预处理算法
export const featureAlgorithms = [ export const featureAlgorithms = [
{ label: 'densifier (数据增稠)', value: 'densifier' },
{ label: 'densifier (缺失值填充)', value: 'densifier' },
{ {
label: 'extra_trees_preproc_for_classification (分类任务极端随机树)',
label: 'extra_trees_preproc_for_classification (特征选择-分类任务极端随机树)',
value: 'extra_trees_preproc_for_classification', value: 'extra_trees_preproc_for_classification',
}, },
{ {
label: 'extra_trees_preproc_for_regression (回归任务极端随机树)',
label: 'extra_trees_preproc_for_regression (特征选择-回归任务极端随机树)',
value: 'extra_trees_preproc_for_regression', value: 'extra_trees_preproc_for_regression',
}, },
{ label: 'fast_ica (快速独立成分分析)', value: 'fast_ica' },
{ label: 'feature_agglomeration (特征聚合)', value: 'feature_agglomeration' },
{ label: 'kernel_pca (核主成分分析)', value: 'kernel_pca' },
{ label: 'kitchen_sinks (随机特征映射)', value: 'kitchen_sinks' },
{ label: 'liblinear_svc_preprocessor (线性svc预处理器)', value: 'liblinear_svc_preprocessor' },
{ label: 'fast_ica (特征选择-快速独立成分分析)', value: 'fast_ica' },
{ label: 'feature_agglomeration (特征变换-特征聚合)', value: 'feature_agglomeration' },
{ label: 'kernel_pca (特征选择-核主成分分析)', value: 'kernel_pca' },
{ label: 'kitchen_sinks (特征变换-随机特征映射)', value: 'kitchen_sinks' },
{
label: 'liblinear_svc_preprocessor (特征选择-线性svc预处理器)',
value: 'liblinear_svc_preprocessor',
},
{ label: 'no_preprocessing (无预处理)', value: 'no_preprocessing' }, { label: 'no_preprocessing (无预处理)', value: 'no_preprocessing' },
{ label: 'nystroem_sampler (尼斯特罗姆采样器)', value: 'nystroem_sampler' },
{ label: 'pca (主成分分析)', value: 'pca' },
{ label: 'polynomial (多项式特征扩展)', value: 'polynomial' },
{ label: 'random_trees_embedding (随机森林特征嵌入)', value: 'random_trees_embedding' },
{ label: 'nystroem_sampler (特征变换-尼斯特罗姆采样器)', value: 'nystroem_sampler' },
{ label: 'pca (特征选择-主成分分析)', value: 'pca' },
{ label: 'polynomial (特征变换-多项式特征扩展)', value: 'polynomial' },
{ label: 'random_trees_embedding (特征变换-随机森林特征嵌入)', value: 'random_trees_embedding' },
{ {
label: 'select_percentile_classification (基于百分位的分类特征选择)',
label: 'select_percentile_classification 特征选择-基于百分位的分类特征选择)',
value: 'select_percentile_classification', value: 'select_percentile_classification',
}, },
{ {
label: 'select_percentile_regression (基于百分位的回归特征选择)',
label: 'select_percentile_regression (特征选择-基于百分位的回归特征选择)',
value: 'select_percentile_regression', value: 'select_percentile_regression',
}, },
{ {
label: 'select_rates_classification (基于比率的分类特征选择)',
label: 'select_rates_classification (特征选择-基于比率的分类特征选择)',
value: 'select_rates_classification', value: 'select_rates_classification',
}, },
{ label: 'select_rates_regression (基于比率的回归特征选择)', value: 'select_rates_regression' },
{ label: 'truncatedSVD (截断奇异值分解)', value: 'truncatedSVD' },
{
label: 'select_rates_regression (特征选择-基于比率的回归特征选择)',
value: 'select_rates_regression',
},
{ label: 'truncatedSVD (特征变换-截断奇异值分解)', value: 'truncatedSVD' },
]; ];

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