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/255755/12057325
m rnnc.m
%RNNC Random Neural Net classifier
%
% W = RNNC(A,N,S)
%
% INPUT
% A Input dataset
% N Number of neurons in the hidden layer (default: 10)
% S Standard deviation of weights in an input lay
www.eeworm.com/read/255755/12058104
m setcost.m
%SETCOST Reset classification cost matrix of mapping
%
% W = SETCOST(W,COST,LABLIST)
%
% The classification cost matrix of the dataset W is reset to COST.
% W has to be a trained classifier. CO
www.eeworm.com/read/253950/12173537
m demknn1.m
%DEMKNN1 Demonstrate nearest neighbour classifier.
%
% Description
% The problem consists of data in a two-dimensional space. The data is
% drawn from three spherical Gaussian distributions with prio
www.eeworm.com/read/339665/12211505
m demknn1.m
%DEMKNN1 Demonstrate nearest neighbour classifier.
%
% Description
% The problem consists of data in a two-dimensional space. The data is
% drawn from three spherical Gaussian distributions with prio
www.eeworm.com/read/150905/12248387
m rnnc.m
%RNNC Random Neural Net classifier
%
% W = RNNC(A,N,S)
%
% INPUT
% A Input dataset
% N Number of neurons in the hidden layer (default: 10)
% S Standard deviation of weights in an input lay
www.eeworm.com/read/150905/12249399
m setcost.m
%SETCOST Reset classification cost matrix of mapping
%
% W = SETCOST(W,COST,LABLIST)
%
% The classification cost matrix of the dataset W is reset to COST.
% W has to be a trained classifier. CO
www.eeworm.com/read/150905/12250444
m demknn1.m
%DEMKNN1 Demonstrate nearest neighbour classifier.
%
% Description
% The problem consists of data in a two-dimensional space. The data is
% drawn from three spherical Gaussian distributions with prio
www.eeworm.com/read/252978/12251988
java linear.java
package learner;
import java.util.Arrays;
public class Linear implements Classifier {
public Data data;
public double threshold;
public double error;
public int sign;
Linear(
www.eeworm.com/read/252978/12251990
java distancemajority.java
package learner;
public class DistanceMajority implements Classifier {
int k;
Data data;
DistanceMajority(Data data, int k) {
this.data = data;
this.k = k;
}
public double tes
www.eeworm.com/read/150760/12265655
m quadclass.m
function [y,dfce]=quadclass( X, model)
% QUADCLASS Quadratic classifier.
%
% Synopsis:
% [y,dfce] = quadclass(X,model)
%
% Description:
% This function classifies input data X using quadratic
% dis