代码搜索：machine learning
找到约 10,000 项符合「machine learning」的源代码
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www.eeworm.com/read/334076/12642594
c learning.c
/* Copyright (c) 1994-98 by The MathWorks, Inc. */
/* $Revision: 1.8 $ $Date: 1997/12/01 21:45:36 $ $Author: moler $ */
/* forward pass from node 'from' to node 'to' */
/* the input vector shou
www.eeworm.com/read/101749/15819405
txt learning.txt
Weights between unit 0 of layer 1 and units of layer 0
-3.179077 -3.130343 -3.170524
Threshold of unit 0 of layer 1 is 1.031570
Weights between unit 1 of layer 1 and units of layer 0
-6.3
www.eeworm.com/read/233789/14136400
pdf michie_-_machine[1].learning,.neural.and.statistical.classification.pdf
www.eeworm.com/read/386950/8716555
m dataforc45.m
%DataForC45.m
%Shiliang Sun, Apr. 8, 2007.
%The data are constructed from Table 3.2 of Mitchell's book:
%Machine Learning.
Traindata=[
7 1 1 1 2
7 1 1 2 2
8 1 1 1 1
www.eeworm.com/read/298374/7964827
m dataforc45.m
%DataForC45.m
%Shiliang Sun, Apr. 8, 2007.
%The data are constructed from Table 3.2 of Mitchell's book:
%Machine Learning.
Traindata=[
7 1 1 1 2
7 1 1 2 2
8 1 1 1 1
www.eeworm.com/read/191902/8417125
m interactive_learning.m
function D = Interactive_Learning(train_features, train_targets, params, region);
% Classify using nearest neighbors and interactive learning
% Inputs:
% features- Train features
% targets - Tr
www.eeworm.com/read/191902/8417409
m competitive_learning.m
function [features, targets, label, W] = Competitive_learning(train_features, train_targets, params, region, plot_on)
% Perform preprocessing using a competitive learning network
% Inputs:
% fea
www.eeworm.com/read/290942/8449688