代码搜索:classification

找到约 3,679 项符合「classification」的源代码

代码结果 3,679
www.eeworm.com/read/386050/8769515

m prtestc.m

%PRTESTC Test routine for the PRTOOLS classifier % % This script tests a given, untrained classifier w, defined in the % workspace, e.g. w = my_classifier. The goal is to find out whether % w fulfill
www.eeworm.com/read/187045/8881392

m pnndemo.m

% PNNDEMO -- Probabilistic Neural Network Demo m-file % Ron Shaffer % Naval Research Laboratory % 3-21-96 % fprintf ('Probabilistic Neural Network Demo \n') fprintf ('Ron Shaffer \n') fprintf (
www.eeworm.com/read/383906/8911847

m pnndemo.m

% PNNDEMO -- Probabilistic Neural Network Demo m-file % Ron Shaffer % Naval Research Laboratory % 3-21-96 % fprintf ('Probabilistic Neural Network Demo \n') fprintf ('Ron Shaffer \n') fprintf (
www.eeworm.com/read/379751/9178630

readme

Libsvm is a simple, easy-to-use, and efficient software for SVM classification and regression. It solves C-SVM classification, nu-SVM classification, one-class-SVM, epsilon-SVM regression, and nu-SVM
www.eeworm.com/read/182566/9199902

java other.java

package Osbert; public class Other extends GalleryPainting { public Other () { classification = "Other"; } } // class Other
www.eeworm.com/read/182566/9199922

java masterpiece.java

package Osbert; public class Masterpiece extends GalleryPainting { public Masterpiece () { classification = "Masterpiece"; } } // class Masterpiece
www.eeworm.com/read/182566/9199931

java masterwork.java

package Osbert; public class Masterwork extends Masterpiece { public Masterwork (){ classification = "Masterwork"; } } // class Masterwork
www.eeworm.com/read/374006/9424083

html documentation.html

Some Basic Audio Features
www.eeworm.com/read/373628/9445612

html randomforest.html

R: Classification and Regression with Random Forest
www.eeworm.com/read/371849/9533324

readme

Libsvm is a simple, easy-to-use, and efficient software for SVM classification and regression. It solves C-SVM classification, nu-SVM classification, one-class-SVM, epsilon-SVM regression, and nu-SVM