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/441245/7673039
m mogc.m
%MOGC Mixture of Gaussian classifier
%
% W = MOGC(A,N)
% W = A*MOGC([],N);
%
% INPUT
% A Dataset
% N Number of mixtures (optional; default 2)
% R,S Regularization parameters, 0
www.eeworm.com/read/441245/7673236
m lssvc.m
function W = lssvc(A, TYPE, PAR, C)
%LSSVC Least-Squares Support Vector Classifier
%
% W = lssvc(A,TYPE,PAR,C);
%
% INPUT
% A dataset
% TYPE Type of the kernel (optional; default: '
www.eeworm.com/read/441245/7673292
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/439518/7706970
m demo.m
%
% DEMONSTRATION OF ADABOOST_tr and ADABOOST_te
%
% Just type "demo" to run the demo.
%
% Using adaboost with linear threshold classifier
% for a two class classification problem.
%
% Bug Reporting:
www.eeworm.com/read/439513/7707448
m demo.m
%
% DEMONSTRATION OF ADABOOST_tr and ADABOOST_te
%
% Just type "demo" to run the demo.
%
% Using adaboost with linear threshold classifier
% for a two class classification problem.
%
% Bug Reporting:
www.eeworm.com/read/299459/7850179
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
www.eeworm.com/read/299459/7850696
m tune_ocr.m
% TUNE_OCR Tunes SVM classifier for OCR problem.
%
% Description:
% The following steps are performed:
% - Training set is created from data in directory ExamplesDir.
% - Multi-class SVM is
www.eeworm.com/read/398324/7994117
m train.m
function net = train(net, tutor, varargin)
% TRAIN
%
% Train a support vector classifier network using the specified tutor.
%
% load data/iris x y;
%
% C = 100;
% kernel = r
www.eeworm.com/read/398324/7994227
m train.m
function net = train(net, tutor, varargin)
% TRAIN
%
% Train a support vector classifier network using the specified tutor.
%
% load data/iris x y;
%
% C = 100;
% kernel = r
www.eeworm.com/read/397106/8067634
m pocket_vccore.m
% Learns classifier and classifies test set
% using the perceptron learning algorithm
% Works with 2 class labels, any number of features
% when the class labels are 0 and 1.
% Invoke using Percep