Java中实现PCA降维

package com.excellence.splitsentence;
import java.net.UnknownHostException;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Collections;
import java.util.List;
import org.jblas.ComplexDoubleMatrix;
import org.jblas.ComplexFloatMatrix;
import org.jblas.DoubleMatrix;
import org.jblas.Eigen;
import org.jblas.FloatMatrix;

import com.mongodb.BasicDBList;
import com.mongodb.DB;
import com.mongodb.DBCollection;
import com.mongodb.DBCursor;
import com.mongodb.MongoClient;
import com.mongodb.MongoCredential;
import com.mongodb.ServerAddress;
public class PCA {
     /**
      * Reduce matrix dimension     减少矩阵维度
      * @param source         源矩阵
      * @param dimension       目标维度
      * @return Target matrix     返回目标矩阵
      */ 

    public static FloatMatrix dimensionReduction(FloatMatrix source, int dimension) {
        //C=X*X^t/m     矩阵*矩阵^异或/列数
        FloatMatrix covMatrix = source.mmul(source.transpose()).div(source.columns);
        ComplexFloatMatrix eigVal = Eigen.eigenvalues(covMatrix);
        ComplexFloatMatrix[] eigVectorsVal = Eigen.eigenvectors(covMatrix);
        ComplexFloatMatrix eigVectors = eigVectorsVal[0];
        //通过特征值将符号向量从大到小排序
        List<PCABean> beans = new ArrayList<PCA.PCABean>();
        for (int i = 0; i < eigVectors.columns; i++) {
            beans.add(new PCABean(eigVal.get(i).real(), eigVectors.getColumn(i)));
        }
        Collections.sort(beans);
        FloatMatrix newVec = new FloatMatrix(dimension, beans.get(0).vector.rows);
        for (int i = 0; i < dimension; i++) {
            ComplexFloatMatrix dm = beans.get(i).vector;
            FloatMatrix real = dm.getReal();
            newVec.putRow(i, real);
        }
        return newVec.mmul(source);
    }
    static class PCABean implements Comparable<PCABean> {
        float eigenValue;
        ComplexFloatMatrix vector;
        public PCABean(Float eigenValue, ComplexFloatMatrix vector) {
            super();
            this.eigenValue = eigenValue;
            this.vector = vector;
        }
        @Override
        public int compareTo(PCABean o) {
            return Float.compare(o.eigenValue, eigenValue);
        }
        @Override
        public String toString() {
            return "PCABean [eigenValue=" + eigenValue + ", vector=" + vector + "]";
        }
    }
}

如何调用？

float[] vector = docvector.getElementArray();
FloatMatrix d = new FloatMatrix(vector);

FloatMatrix result = PCA.dimensionReduction(d, 10);