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/425699/10336306
m go_classify.m
% Perform classification using Nister-like method
% AUTORIGHTS
% Copyright (C) 2006 Regents of the University of California
% All rights reserved
%
% Written by Andrea Vedaldi (UCLA VisionLab).
%
%
www.eeworm.com/read/159921/10587882
m contents.m
% Statistical Pattern Recognition Toolbox.
%
% Contents
%
% bayes - (dir) Bayes classification.
% datasets - (dir) Functions for handling with data sets.
% generalp - (dir) General purpose
www.eeworm.com/read/159921/10588603
m~ contents.m~
% Statistical Pattern Recognition Toolbox.
%
% Contents
%
% bayes - (dir) Bayes classification.
% datasets - (dir) Functions for handling with data sets.
% generalp - (dir) General purpose
www.eeworm.com/read/351797/10609669
m getbias.m
function bias = getbias(net)
% GETBIAS
%
% Accessor method returning the bias of a support vector classification
% network.
%
% bias = getbias(net);
%
% File : @svc/getbias.m
%
www.eeworm.com/read/351797/10609784
m svctutor.m
function tutor = svctutor(arg)
% SVCTUTOR
%
% Constructor for a class of tutor objects used to train support vector
% classification networks. Note this is an abstract base class, you cannot
%
www.eeworm.com/read/421949/10676570
m contents.m
% Statistical Pattern Recognition Toolbox.
%
% Contents
%
% bayes - (dir) Bayes classification.
% datasets - (dir) Functions for handling with data sets.
% generalp - (dir) General purpose
www.eeworm.com/read/421949/10677297
m~ contents.m~
% Statistical Pattern Recognition Toolbox.
%
% Contents
%
% bayes - (dir) Bayes classification.
% datasets - (dir) Functions for handling with data sets.
% generalp - (dir) General purpose
www.eeworm.com/read/349842/10796654
m genetic_programming.m
function [D, best_fun] = genetic_programming(features, targets, params, region)
% A genetic programming algorithm for classification
%
% features - Train features
% targets - Train targets
www.eeworm.com/read/418695/10935152
m spatm.m
%SPATM Augment image dataset with spatial label information
%
% E = spatm(D,s)
%
% If D = A*W*classc, the output of a classification of a dataset A
% containing feature images, then E is and augmented
www.eeworm.com/read/418695/10935212
m polyc.m
%POLYC Polynomial Classification
%
% W = polyc(A,classf,n,s)
%
% Adds polynomial features to the dataset A and runs the untrained
% classifier classf. n is the degree of the polynome (default 1).