本文整理汇总了Java中org.jblas.FloatMatrix.dot方法的典型用法代码示例。如果您正苦于以下问题：Java FloatMatrix.dot方法的具体用法？Java FloatMatrix.dot怎么用？Java FloatMatrix.dot使用的例子？那么恭喜您, 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.FloatMatrix的用法示例。
在下文中一共展示了FloatMatrix.dot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: predict
import org.jblas.FloatMatrix; //导入方法依赖的package包/类
public float predict(SparseVector sparseVector) {
float predicted = 0.0f;
for (int i = 0; i < sparseVector.size(); ++i) {
// linear term
SparseVector.SparseEntry entryA = sparseVector.get(i);
int keyA = entryA.key;
float valueA = entryA.value;
FloatMatrix vectorA = latentVectors[keyA];
predicted += valueA * biases.get(keyA);
// quadratic term
// XXX(od): do not include quadratic features
for (int j = i + 1; j < sparseVector.size(); ++j) {
SparseVector.SparseEntry entryB = sparseVector.get(j);
int keyB = entryB.key;
float valueB = entryB.value;
FloatMatrix vectorB = latentVectors[keyB];
predicted += valueA * valueB * vectorA.dot(vectorB);
}
}
return predicted;
}
示例2: cosine
import org.jblas.FloatMatrix; //导入方法依赖的package包/类
public static double cosine(FloatMatrix a, FloatMatrix b) {
double normA = Math.pow(a.norm2(), 2);
double normB = Math.pow(b.norm2(), 2);
return a.dot(b) / (Math.sqrt(normA) * Math.sqrt(normB));
}
示例3: gradientLength
import org.jblas.FloatMatrix; //导入方法依赖的package包/类
public float gradientLength(FloatMatrix gradient) {
return gradient.dot(gradient) / (float) gradient.length;
}
示例4: cosineSimilarity
import org.jblas.FloatMatrix; //导入方法依赖的package包/类
/**
* Computes and returns the cosine similarity of two word vectors
* @param vec1 the first float vector
* @param vec2 the second float vector
* @return the cosine similarity of the two word vectors
*/
public static double cosineSimilarity(FloatMatrix vec1, FloatMatrix vec2) {
return vec1.dot(vec2);
}
示例5: cosine
import org.jblas.FloatMatrix; //导入方法依赖的package包/类
/**
* Computes the cosine similarity between two vectors.
* @param a first input vector
* @param b second input vector
* @return cosine similarity metric between a and b
*/
public static double cosine(FloatMatrix a, FloatMatrix b) {
double normA = Math.pow(a.norm2(), 2);
double normB = Math.pow(b.norm2(), 2);
return a.dot(b) / (Math.sqrt(normA) * Math.sqrt(normB));
}