Q matrices for various formulations

LR Bayes SVM XGB decisian tree random forest ...

A CNN for text classification. Uses an embedding layer, followed by a convolutional, max-pooling and softmax layer.

Kernel Cache l is the number of total data items size is the cache size limit in bytes

Kernel evaluation the static method k_function is for doing single kernel evaluation the constructor of Kernel prepares to calculate the l*l kernel m

An SMO algorithm in Fan et al., JMLR 6(2005), p. 1889--1918 Solves: min 0.5(\alpha^T Q \alpha) + p^T \alpha y^T \alpha = \delta y_i = +1 or -1 0 <=

Solver for nu-svm classification and regression additional constraint: e^T \alpha = constant

decision_function

svm_model