代码搜索：classification
找到约 3,679 项符合「classification」的源代码
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www.eeworm.com/read/486842/6530672
c maxent.c
/* Weight-setting and scoring implementation for Maximum Entropy classification */
/* Copyright (C) 1997, 1998, 1999 Andrew McCallum
Written by: Kamal Nigam (knigam@cs.cmu.edu>
This file is
www.eeworm.com/read/485544/6552780
m demglm1.m
%DEMGLM1 Demonstrate simple classification using a generalized linear model.
%
% Description
% The problem consists of a two dimensional input matrix DATA and a
% vector of classifications T. The da
www.eeworm.com/read/485544/6552812
m demglm2.m
%DEMGLM2 Demonstrate simple classification using a generalized linear model.
%
% Description
% The problem consists of a two dimensional input matrix DATA and a
% vector of classifications T. The da
www.eeworm.com/read/478547/6709473
m cart.m
function D = CART(train_features, train_targets, params, region)
% Classify using classification and regression trees
% Inputs:
% features - Train features
% targets - Train targets
% para
www.eeworm.com/read/410924/11265014
m cart.m
function D = CART(train_features, train_targets, params, region)
% Classify using classification and regression trees
% Inputs:
% features - Train features
% targets - Train targets
% para
www.eeworm.com/read/400577/11573188
m costm.m
%COSTM Cost mapping, classification using costs
%
% Y = COSTM(X,C,LABLIST)
% W = COSTM([],C,LABLIST)
%
% DESCRIPTION
% Maps the classifier output X (assumed to be posterior probability
% estimate
www.eeworm.com/read/347853/11631357
pro gni91220.pro
/*Copyright (c) 1986, 88 by Borland International, Inc.
*/
code = 4000
/*This is a small example of how to create a
classification expert-system in TURBO-
Prolog.
Animals are classified in
www.eeworm.com/read/255755/12057980
m costm.m
%COSTM Cost mapping, classification using costs
%
% Y = COSTM(X,C,LABLIST)
% W = COSTM([],C,LABLIST)
%
% DESCRIPTION
% Maps the classifier output X (assumed to be posterior probability
% estimate
www.eeworm.com/read/253950/12173740
m demglm1.m
%DEMGLM1 Demonstrate simple classification using a generalized linear model.
%
% Description
% The problem consists of a two dimensional input matrix DATA and a
% vector of classifications T. The da
www.eeworm.com/read/253950/12174236
m demglm2.m
%DEMGLM2 Demonstrate simple classification using a generalized linear model.
%
% Description
% The problem consists of a two dimensional input matrix DATA and a
% vector of classifications T. The da