Description: The Principal component analysis, is a standard technique used for data reduction in statistical pattern recognition and signal processing
A common problem in statistical pattern recognition is feature selection or feature extraction. Feature selection is a process whereby a data space is transformed into a feature space that theory has exactly same dimension as the original data space. However the transformation is designed in such a way that the data set is represented by a reduced number of “effective features” and most of the intrinsic information content of the data or the data set undergoes a dimensionality reduction.
PCA Platform: |
Size: 13312 |
Author:binu |
Hits:
Description: 经典特征选择程序，在特征提取完成后进行特征选择可以达到提取有用成分的目的-Feature selection procedure, after completion of the feature extraction feature selection can achieve the purpose of extracting useful components Platform: |
Size: 7168 |
Author:yangxi |
Hits:
Description: meta biomarker code matlab for feature s selection uses filer methods Relief and mrmr with svm and knn like classifier for validation Platform: |
Size: 2048 |
Author:karima |
Hits:
Description: Relief算法是一种特征权重算法,可以用于特征选择-Relief algorithm is a feature weighting algorithm，which can be used for feature selection Platform: |
Size: 787456 |
Author:谈文艺 |
Hits:
Description: matlab基于Relief算法的特征权重选择，有效地选择出了权重数据(Based on the feature weight selection of Relief algorithm, the weighting data are effectively selected) Platform: |
Size: 708608 |
Author:sunsy
|
Hits:
Search - FEATURE SELECTION RELIEF