Complexity / 2017 / Article / Alg 1

Research Article

Kernel Negative ε Dragging Linear Regression for Pattern Classification

Algorithm 1

Input: Training samples matrix ; Label matrix ; dragging coefficient matrix ; test
sample ; parameter ;
Output: the slack variable class label matrix ; predicted class for test sample ;
Initialization: ;
Calculate ;
Set threshold ; Set .
Repeat
Given , calculate .
Utilize , then calculate .
Until the absolute value of the difference between objective functions of two consecutive
loops is smaller than threshold .
For test sample , calculate .
If , then is classified into the th class. is the th entry of .
Output: the transformation matrix , .

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