代码搜索：classifier
找到约 4,824 项符合「classifier」的源代码
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www.eeworm.com/read/150905/12248413
m bpxnc.m
%BPXNC Back-propagation trained feed-forward neural net classifier
%
% [W,HIST] = BPXNC (A,UNITS,ITER,W_INI,T,FID)
%
% INPUT
% A Dataset
% UNITS Array indicating number of units in each h
www.eeworm.com/read/150905/12249152
m roc.m
%ROC Receiver-Operator Curve
%
% E = ROC(A,W,C,N)
% E = ROC(B,C,N)
%
% INPUT
% A Dataset
% W Trained classifier, or
% B Classification result, B = A*W*CLASSC
% C Index of desired clas
www.eeworm.com/read/149739/12352771
m bpxnc.m
%BPXNC Back-propagation trained feed-forward neural net classifier
%
% [W,HIST] = BPXNC (A,UNITS,ITER,W_INI,T,FID)
%
% INPUT
% A Dataset
% UNITS Array indicating number of units in each h
www.eeworm.com/read/149739/12353497
m roc.m
%ROC Receiver-Operator Curve
%
% E = ROC(A,W,C,N)
% E = ROC(B,C,N)
%
% INPUT
% A Dataset
% W Trained classifier, or
% B Classification result, B = A*W*CLASSC
% C Index of desired clas
www.eeworm.com/read/131774/14130060
java bayesiannaive.java
/*
Bao Jie 2002-04-02
Iowa State University
*/
package weka.classifiers;
import java.io.*;
import java.util.*;
import weka.core.*;
public class BayesianNaive extends Classifier {// for
www.eeworm.com/read/128468/14295521
m msvmclass.m
function [Ipred,mfpred] = msvmclass(Xtst,Xtrn,Itrn,malpha,mbias,ker,arg,info)
% MSVMCLASS muli-class version of the SVM classifier.
% [Ipred,mfpred] = msvmclass(Xtst,Xtrn,Itrn,malpha,mbias,ker,arg,in
www.eeworm.com/read/218623/14912090
m mil_run.m
function run = MIL_run(classifier)
warning('off','MATLAB:colon:operandsNotRealScalar');
% clear global preprocess;
global preprocess;
global temp_train_file temp_test_file temp_output_file te
www.eeworm.com/read/13871/284607
m knnfwd.m
function [y, l] = knnfwd(net, x)
%KNNFWD Forward propagation through a K-nearest-neighbour classifier.
%
% Description
% [Y, L] = KNNFWD(NET, X) takes a matrix X of input vectors (one vector
% pe
www.eeworm.com/read/13911/286781
m svmtrain.m
function net = svmtrain(net, X, Y, alpha0, dodisplay)
% SVMTRAIN - Train a Support Vector Machine classifier
%
% NET = SVMTRAIN(NET, X, Y)
% Train the SVM given by NET using the training data X wi
www.eeworm.com/read/209211/4986287
h graffiti.h
#define NUM_RECS 3
#define DEFAULT_REC_DIR "classsifiers"
#define REC_DEFAULT_USER_DIR "/sys/lib/scribble/classifiers"
#define CLASSIFIER_DIR "lib/classifiers"
#define DEFAULT_