中文说明：pca做特征降维，然后进行特征空间随机分割构造多个svm分类器，并行处理，对样本进行分类，基于特征空间的svm多分类器
English Description：
PCA is used to reduce the dimension of features, and then the feature space is randomly divided to construct multiple SVM classifiers, which are processed in parallel to classify the samples. SVM multi classifiers based on feature space are proposed