代码搜索：Classifier
找到约 4,824 项符合「Classifier」的源代码
代码结果 4,824
www.eeworm.com/read/386050/8768350
m ldc.m
%LDC Linear Bayes Normal Classifier (BayesNormal_1)
%
% [W.R,S,M] = LDC(A,R,S,M)
% W = A*LDC([],R,S,M);
%
% INPUT
% A Dataset
% R,S Regularization parameters, 0
www.eeworm.com/read/418695/10935172
m persc.m
%PERSC Linear classifier by non-linear perceptron
%
% [W1,W2] = persc(A,n,step,target,W)
%
% Finds the linear discriminant function W1 (a mapping) by n cycles
% of the data through the non-linear
www.eeworm.com/read/299984/7140368
m ldc.m
%LDC Linear Bayes Normal Classifier (BayesNormal_1)
%
% [W.R,S,M] = LDC(A,R,S,M)
% W = A*LDC([],R,S,M);
%
% INPUT
% A Dataset
% R,S Regularization parameters, 0
www.eeworm.com/read/460435/7250843
m ldc.m
%LDC Linear Bayes Normal Classifier (BayesNormal_1)
%
% [W.R,S,M] = LDC(A,R,S,M)
% W = A*LDC([],R,S,M);
%
% INPUT
% A Dataset
% R,S Regularization parameters, 0
www.eeworm.com/read/441245/7673057
m ldc.m
%LDC Linear Bayes Normal Classifier (BayesNormal_1)
%
% [W.R,S,M] = LDC(A,R,S,M)
% W = A*LDC([],R,S,M);
%
% INPUT
% A Dataset
% R,S Regularization parameters, 0
www.eeworm.com/read/397106/8067881
m construct_svm.m
function net = construct_svm(nin, kernel, kernelpar, C, use2norm, qpsolver, qpsize)
% SVM - Create a Support Vector Machine classifier
%
% NET = SVM(NIN, KERNEL, KERNELPAR, C, USE2NORM, QPSOLVER, Q
www.eeworm.com/read/397102/8067985
m persc.m
%PERSC Linear classifier by non-linear perceptron
%
% [W1,W2] = persc(A,n,step,target,W)
%
% Finds the linear discriminant function W1 (a mapping) by n cycles
% of the data through the non-linear
www.eeworm.com/read/143004/12905302
pas scs.pas
program scs;
{ SCS - A Simple Classifier System }
{ (C) David E. Goldberg, 1987 }
{ All Rights Reserved }
{$I declare.scs }
{$I random.apb }
{$I io.scs }
{$I utility.scs }
{$I e
www.eeworm.com/read/139298/5803175
java knearestneighbor.java
package fasbir.classifiers;
import java.io.Serializable;
import java.util.Arrays;
import java.util.Comparator;
import java.util.Enumeration;
import weka.classifiers.Classifier;
import weka.c
www.eeworm.com/read/264146/11327616
m mlknn_train.m
function [Prior,PriorN,Cond,CondN]=MLKNN_train(train_data,train_target,Num,Smooth)
%MLKNN_train trains a multi-label k-nearest neighbor classifier
%
% Syntax
%
% [Prior,PriorN,Cond,CondN