计算机工程与设计
計算機工程與設計
계산궤공정여설계
COMPUTER ENGINEERING AND DESIGN
2009年
21期
4931-4935
,共5页
特征%聚类%PLS%回归%预测
特徵%聚類%PLS%迴歸%預測
특정%취류%PLS%회귀%예측
feature%clustering%PLS%regression%prediction
特征选择应尽可能考虑特征的预测能力、特征间的相关性以及算法的计算效率等因素.由于目前Filter和Wrapper两类特征选择方法均存在着缺陷,提出了一种适用于回归的基于层次聚类算法和偏最小二乘的特征选择方法,它不但能选取出预测能力较强的特征,而且使选出的特征间的相关性低.仿真实验表明,将该方法用于盾构隧道施工地面沉降的回归预测中,所选取的最优特征子集使回归模型的精度得到提高,训练时间明显下降.
特徵選擇應儘可能攷慮特徵的預測能力、特徵間的相關性以及算法的計算效率等因素.由于目前Filter和Wrapper兩類特徵選擇方法均存在著缺陷,提齣瞭一種適用于迴歸的基于層次聚類算法和偏最小二乘的特徵選擇方法,它不但能選取齣預測能力較彊的特徵,而且使選齣的特徵間的相關性低.倣真實驗錶明,將該方法用于盾構隧道施工地麵沉降的迴歸預測中,所選取的最優特徵子集使迴歸模型的精度得到提高,訓練時間明顯下降.
특정선택응진가능고필특정적예측능력、특정간적상관성이급산법적계산효솔등인소.유우목전Filter화Wrapper량류특정선택방법균존재착결함,제출료일충괄용우회귀적기우층차취류산법화편최소이승적특정선택방법,타불단능선취출예측능력교강적특정,이차사선출적특정간적상관성저.방진실험표명,장해방법용우순구수도시공지면침강적회귀예측중,소선취적최우특정자집사회귀모형적정도득도제고,훈련시간명현하강.
There are some important factors should be considered in feature selection, such as the predictive ablity of feature, the correlation between features and the computing cost of algorithm. Due to the insufficiencies of both filter and wrapper feature selection methods, a feature selection method is presented based on hierarchical clustering algorithm and partial least squares. It not only select some high predictive features, but also keep the low correlation of features. This method is used in the regressive prediction of ground sedimentation in shield tunneling process. The simulation experiment shows that the optimal feature subset contributes to higher precision of regression model and lower training time.
