feature selection

基本解釋

Feature selection is an important part of data processing.
特征選擇是數(shù)據(jù)處理的一項(xiàng)重要內(nèi)容。
It is also important to think about feature selection for training the model.
在訓(xùn)練模型時(shí)考慮使用特征選擇也是很重要的。
Feature selection and feature extraction are common methods for dimensionality reduction.
特征選擇和特征抽取是維數(shù)約簡常用的兩種方法。

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特征選擇
Research on balanced feature selection algorithm.
2、均衡特征選擇算法研究。
特征選取
With the research of two common methods: feature filtering and feature selection, a new algorithm based on minimum class difference is proposed.
結(jié)合對(duì)單詞過濾與特征選取兩類常用預(yù)處理方法的研究，本文提出了基于最小類差異的特征過濾算法。
電子、通信與自動(dòng)控制技術(shù)
特征選取

屬性篩選
特征挑選
Experiment results showed that feature selection methods can improve predictive abilities of classifiers.
研究結(jié)果均顯示,使用特征挑選方法能夠有效地提高分類器的預(yù)測(cè)能力。
數(shù)學(xué)
特征選擇
特點(diǎn)選擇