本文整理汇总了Java中org.jblas.DoubleMatrix.putColumn方法的典型用法代码示例。如果您正苦于以下问题：Java DoubleMatrix.putColumn方法的具体用法？Java DoubleMatrix.putColumn怎么用？Java DoubleMatrix.putColumn使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类org.jblas.DoubleMatrix的用法示例。
在下文中一共展示了DoubleMatrix.putColumn方法的5个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Java代码示例。
示例1: normalize
import org.jblas.DoubleMatrix; //导入方法依赖的package包/类
public DoubleMatrix normalize(DoubleMatrix A) {
DoubleMatrix B = new DoubleMatrix(A.rows, A.columns);
DoubleMatrix max = A.columnMaxs();
DoubleMatrix min = A.columnMins();
logger.info("Normalizing hypercube into [0,1]^n...");
for(int j=0; j<B.columns; j++) {
double mx = max.get(j);
double mn = min.get(j);
if(mx == mn) {
B.putColumn(j, DoubleMatrix.zeros(A.rows, 1));
continue;
}
for(int i=0; i<B.rows; i++)
B.put(i, j, (A.get(i, j) - mn) / (mx - mn));
}
save("C"+B.columns, B);
return B;
}
示例2: pca
import org.jblas.DoubleMatrix; //导入方法依赖的package包/类
/**
*
*
* @param A
* @param dim
* @return
*/
public DoubleMatrix pca(DoubleMatrix A, int dim) {
logger.info("Type 'pca' started (target dimensions = "+dim+").");
A = centerData(A);
save("A", A);
logger.info("Computing SVD...");
DoubleMatrix[] usv = Singular.fullSVD(A);
DoubleMatrix U = usv[0];
DoubleMatrix S = usv[1];
save("U", U);
save("S", S);
//
logger.info("Reducing U to Uk...");
DoubleMatrix Uk = new DoubleMatrix(U.rows, dim);
for(int i=0; i<dim; i++)
Uk.putColumn(i, U.getColumn(i));
save("Uk", Uk);
// build S matrix
logger.info("Reducing S to Sk...");
DoubleMatrix Sk = new DoubleMatrix(dim, dim);
for (int i = 0; i < dim; i++) {
Sk.put(i, i, S.get(i));
}
save("Sk", Sk);
// calculate principal component matrix...
logger.info("Computing principal components...");
DoubleMatrix B = Uk.mmul(Sk);
save("B", B);
return B;
}
示例3: reconstruct2
import org.jblas.DoubleMatrix; //导入方法依赖的package包/类
public DoubleMatrix reconstruct2(DoubleMatrix A, int k) {
logger.info("Type 'reconstruct2' started...");
A = centerData(A);
save("A", A);
DoubleMatrix[] usv = Singular.fullSVD(A);
// n x n
DoubleMatrix U = usv[0];
// n x p
DoubleMatrix S = usv[1];
// p x p (straight)
DoubleMatrix V = usv[2];
save("U", U);
save("S", S);
save("V", V);
for(int i = k; i < U.columns; i++)
U.putColumn(i, DoubleMatrix.zeros(U.rows, 1));
save("Uk", U);
DoubleMatrix Sm = new DoubleMatrix(A.rows, A.columns);
for (int i = 0; i < k; i++) {
Sm.put(i, i, S.get(i));
}
save("Sk", Sm);
// for (int i = k; i < V.rows; i++) {
// V.putColumn(i, DoubleMatrix.zeros(1, V.columns));
// }
// visual("Vk", V);
//
DoubleMatrix Aapprox = U.mmul(Sm).mmul(V.transpose());
save("Aapprox", Aapprox);
return Aapprox;
}
示例4: getInputMatrix
import org.jblas.DoubleMatrix; //导入方法依赖的package包/类
private DoubleMatrix getInputMatrix() {
DoubleMatrix result = new DoubleMatrix(inputNeurons, BATCH_SIZE);
for (int i=0; i < BATCH_SIZE; i++) {
replay = replayMemory.getRandom();
result.putColumn(i, replay.getState());
if (replay.getReward() == 0) {
expectedValue[i] = replay.getReward() + gamma * targetNetwork.forwardPropagate(replay.getNextState()).max();
} else {
expectedValue[i] = replay.getReward();
}
replays[i] = replay;
}
return result;
}
示例5: reconstruct
import org.jblas.DoubleMatrix; //导入方法依赖的package包/类
/**
* @param A
* @param k
* @return
*/
public DoubleMatrix reconstruct(DoubleMatrix A, int k) {
logger.info("Type 'reconstruct' started...");
A = centerData(A);
save("A", A);
DoubleMatrix[] usv = Singular.fullSVD(A);
// n x n
DoubleMatrix U = usv[0];
// n x p
DoubleMatrix S = usv[1];
// p x p (straight)
DoubleMatrix V = usv[2];
save("U", U);
save("S", S);
save("V", V);
// n x k
DoubleMatrix Uk = new DoubleMatrix(U.rows, k);
for(int i=0; i<k; i++)
Uk.putColumn(i, U.getColumn(i));
save("Uk", Uk);
// k x k
DoubleMatrix Sk = new DoubleMatrix(k, k);
for (int i = 0; i < k; i++) {
Sk.put(i, i, S.get(i));
}
save("Sk", Sk);
// p x k (straight)
DoubleMatrix Vk = new DoubleMatrix(A.columns, k);
for (int i = 0; i < k; i++) {
Vk.putColumn(i, V.getColumn(i));
}
save("Vk", Vk);
//
DoubleMatrix Aapprox = Uk.mmul(Sk).mmul(Vk.transpose());
save("Aapprox", Aapprox);
DoubleMatrix Areduced = new DoubleMatrix(A.rows, k);
for(int i=0; i<k; i++)
Areduced.putColumn(i, Aapprox.getColumn(i));
save("C"+k, Areduced);
return Areduced;
}