使用Fisher线性判别方法的提取分类器
사용Fisher선성판별방법적제취분류기
Using Fisher linear discriminant analysis to extracting classifiers
  • 万方数据
    计算机工程与应用 계산궤공정여응용
    COMPUTER ENGINEERING AND APPLICATIONS
    2010年 14期 132-134 ,共3页

    李文斌%陈嶷瑛%张娟%张新东

    리문빈%진억영%장연%장신동

    机器学习%数据挖掘%文本处理%分类 機器學習%數據挖掘%文本處理%分類
    궤기학습%수거알굴%문본처리%분류
    machine learning%data mining%text processing%classification
    为了消除个体分类器问的相关性,提高集成器分类性能及稳定性,提出了基于Fisher线性判别方法的分类器提取方法.该方法将高维分类器空间压缩至低维分类器空间,并在该空间内学习集成器.在多个数据集上的比较实验结果表明,该方法可行,其集成性能较理想.
    위료소제개체분류기문적상관성,제고집성기분류성능급은정성,제출료기우Fisher선성판별방법적분류기제취방법.해방법장고유분류기공간압축지저유분류기공간,병재해공간내학습집성기.재다개수거집상적비교실험결과표명,해방법가행,기집성성능교이상.
    In order to eliminate relativity between ensembled classifiers and improve effect and stability of combiner,an approach extracting classifiers based on Fisher linear discriminant analysis is proposed.It can reduce classifier space with high dimension,and then learn a combiner in lower dimension space.The compared results obtained on multiple public avaiable datasets show that the method is feasible.lts performance is perfect.
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