MATLAB中的特征选择 [英] Feature Selection in MATLAB
问题描述
我有一个准备用于MATLAB的文本分类数据集.每个文档都是该数据集中的一个向量，并且该向量的维数非常高.在这些情况下，peopl通常会对向量进行某些特征选择，例如您实际找到的WEKA工具包. MATLAB中有类似的东西吗?如果不能，那么我可以建议我做些什么...吗? 谢谢
I have a dataset for text classification ready to be used in MATLAB. Each document is a vector in this dataset and the dimensionality of this vector is extremely high. In these cases peopl usually do some feature selection on the vectors like the ones that you have actually find the WEKA toolkit. Is there anything like that in MATLAB? if not can u suggest and algorithm for me to do it...? thanks
推荐答案
MATLAB(及其工具箱)包括许多处理功能选择的功能:
MATLAB (and its toolboxes) include a number of functions that deal with feature selection:
- RANDFEATURES (生物信息学工具箱):生成功能的随机子集由分类器指导
- RANKFEATURES (生物信息学工具箱):按类可分离性对要素进行排名条件
- SEQUENTIALFS (统计工具箱):顺序特征选择
- RELIEFF (统计工具箱):救济F算法
- TREEBAGGER.OOBPermutedVarDeltaError ，
- RANDFEATURES (Bioinformatics Toolbox): Generate randomized subset of features directed by a classifier
- RANKFEATURES (Bioinformatics Toolbox): Rank features by class separability criteria
- SEQUENTIALFS (Statistics Toolbox): Sequential feature selection
- RELIEFF (Statistics Toolbox): Relief-F algorithm
- TREEBAGGER.OOBPermutedVarDeltaError, predictorImportance (Statistics Toolbox): Using ensemble methods (bagged decision trees)
您还可以找到示例来说明在实际数据集上的用法:
You can also find examples that demonstrates usage on real datasets:
- Identifying Significant Features and Classifying Protein Profiles
- Genetic Algorithm Search for Features in Mass Spectrometry Data
此外，还存在第三方工具箱:
In addition, there exist third-party toolboxes:
- Matlab Toolbox for Dimensionality Reduction
- LIBGS: A MATLAB Package for Gene Selection
否则，您总是可以直接从MATLAB中从WEKA调用您喜欢的函数，因为它包含JVM ...
Otherwise you can always call your favorite functions from WEKA directly from MATLAB since it include a JVM...
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