Label relationshipsMulti-label feature selection is an efficient technique to alleviate the high dimensionality for multi-label learning. Existing multi-label feature selection methods based on information theor
Li L,Liu H,Ma Z,et al.Multi-label feature selectionvia information gain[M].Advanced data mining andapplications.[S.l.]:Springer International Publishing,2014:345-355.Li L, Liu H, Ma Z, Mo Y, Duan Z, Zhou J, Zhao J (2014) Multi-label feature selection via information gain. In: ...
特征选择(feature selection)使用sklearn的Lasso, 数据集使用sklearn的breast cancer。数据准备 importnumpy...
To address this issue, we propose a novel feature selection method named Feature Selection considering Shared Common Mode between features and labels (SCMFS). First, we utilize Coupled Matrix Factorization (CMF) to extract the shared common mode between the feature matrix and the label matrix, ...
Multi-LabelInformedFeatureSelectionLingJian1,2∗,JundongLi1∗,KaiShu1,HuanLiu11.ComputerScienceandEngineering,ArizonaStateUnivers..
主要的Strategy大致可以分为三类：First-Order Strategy: 考虑的是label之间相互独立，那么就可以把Multi-...
As in the traditional single-label classification, the feature selection plays an important role in the multi-label classification. This paper presents a multi-label feature selection algorithm MLFS which consists of two steps. The first step employs the mutual information to complete the local featur...
transforming the input vector into feature vector of length di, fSi:X→Rdi where di is the length of the feature vector of source i(2) A classifier hSi:Rdi→RM from the feature vector into the output label, Ysi. This forms the hypothesis function. ...
In this work we study how conventional feature selection methods can be applied to Hierarchical Multi-label Classification Problems. In Hierarchical Multi-label Classification, instances can belong to two or more classes (labels) simultaneously, where such classes are hierarchically structured. Feature sel...
Feature selection is one of the important pre-processing methods for dimensionality reduction in multi-label learning tasks, which has attracted extensive attention in recent years. Most of the existing approaches transform feature data into the label space during the feature-label mapping process by ...