Feature selection
In machine learning and statistics, feature selection, also known as variable selection, attribute selection or variable subset selection, is the process of selecting a subset of relevant features (variables, predictors) for use in model construction. Feature selection techniques are used for three reasons:
* simplification of models to make them easier to interpret by researchers/users,
* shorter training times,
* enhanced generalization by reducing overfitting(formally, reduction of variance)
primaryTopic
Feature selection
In machine learning and statistics, feature selection, also known as variable selection, attribute selection or variable subset selection, is the process of selecting a subset of relevant features (variables, predictors) for use in model construction. Feature selection techniques are used for three reasons:
* simplification of models to make them easier to interpret by researchers/users,
* shorter training times,
* enhanced generalization by reducing overfitting(formally, reduction of variance)
has abstract
25بك المحتوى هنا ينقصه الاستشه ...... يانات وعلاقتها مع بعضها البعض.
@ar
Die Feature Subset Selection ( ...... an Datensätzen vorhanden ist.
@de
In machine learning and statis ...... w tens to hundreds of samples.
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在机器学习和统计学中，特征选择 也被称为变量选择、属性选择 ...... 微阵列数据，这些场景下特征成千上万，但样本只有几十到几百个。
@zh
特徴選択（とくちょうせんたく、英: feature sele ...... といった点について、人間が理解しやすくなるという効果もある。
@ja
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25بك المحتوى هنا ينقصه الاستشه ...... يانات وعلاقتها مع بعضها البعض.
@ar
Die Feature Subset Selection ( ...... an Datensätzen vorhanden ist.
@de
In machine learning and statis ...... rmally, reduction of variance)
@en
在机器学习和统计学中，特征选择 也被称为变量选择、属性选择 ...... 微阵列数据，这些场景下特征成千上万，但样本只有几十到几百个。
@zh
特徴選択（とくちょうせんたく、英: feature sele ...... といった点について、人間が理解しやすくなるという効果もある。
@ja
label
Feature Subset Selection
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Feature selection
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اختيار المميزات
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特征选择
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特徴選択
@ja