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/367182/2853653
c s_fpclassifyl.c
/* Return classification value corresponding to argument.
Copyright (C) 1997, 2000, 2002 Free Software Foundation, Inc.
This file is part of the GNU C Library.
Contributed by Ulrich Drepper
www.eeworm.com/read/359369/2978526
m confmat.m
function [C,rate]=confmat(Y,T)
%CONFMAT Compute a confusion matrix.
%
% Description
% [C, RATE] = CONFMAT(Y, T) computes the confusion matrix C and
% classification performance RATE for the predi
www.eeworm.com/read/359369/2978537
m demmlp2.m
%DEMMLP2 Demonstrate simple classification using a multi-layer perceptron
%
% Description
% The problem consists of input data in two dimensions drawn from a
% mixture of three Gaussians: two of w
www.eeworm.com/read/160391/5571189
m hmemenu.m
% dataset -> (1=>user data) or (2=>toy example)
% type -> (1=> Regression model) or (2=>Classification model)
% num_glevel -> number of hidden nodes in the net (gating levels)
% num_
www.eeworm.com/read/474600/6813520
m multialgorithms_commands.m
function multialgorithms_commands(command)
%This function processes events from the multi-algorithm GUI screen
switch(command)
case 'Init'
Algorithms = read_algorithms('Classification.tx
www.eeworm.com/read/471358/6890737
m svcinfo.m
function svcinfo(trn,tst,ker,alpha,bias)
%SVCINFO Support Vector Classification Results
%
% Usage: svcinfo(trn,tst,ker,alpha,bias)
%
% Parameters: trn - Training set
% tst - Test
www.eeworm.com/read/195441/8155612
m char3.m
%% Character Recognition Example (III):Training a Simple NN for
%% classification
%% Read the image
I = imread('sample.bmp');
%% Image Preprocessing
img = edu_imgpreprocess(I);
for cnt = 1:5
www.eeworm.com/read/195133/8172757
m svcinfo.m
function svcinfo(trn,tst,ker,alpha,bias)
%SVCINFO Support Vector Classification Results
%
% Usage: svcinfo(trn,tst,ker,alpha,bias)
%
% Parameters: trn - Training set
% tst - Test
www.eeworm.com/read/294863/8197280
m svcinfo.m
function svcinfo(trn,tst,ker,alpha,bias)
%SVCINFO Support Vector Classification Results
%
% Usage: svcinfo(trn,tst,ker,alpha,bias)
%
% Parameters: trn - Training set
% tst - Test
www.eeworm.com/read/393534/8277267
m svcinfo.m
function svcinfo(trn,tst,ker,alpha,bias)
%SVCINFO Support Vector Classification Results
%
% Usage: svcinfo(trn,tst,ker,alpha,bias)
%
% Parameters: trn - Training set
% tst - Test