Description: C4.5Rule-PANE is a rule learning method which could generate accurate and comprehensible symbolic rules, through regarding a neural network ensemble as a pre-process of a rule inducer. Reference: Z.-H. Zhou and Y. Jiang. Medical diagnosis with C4.5 rule preceded by artificial neural network ensemble. IEEE Transactions on Information Technology in Biomedicine, 2003, vol.7, no.1, pp.37-42. 使用神經(jīng)網(wǎng)絡集成方法診斷糖尿病,肝炎,乳腺癌癥的案例研究.
標簽： comprehensibl Description Rule-PANE accurate
上傳時間： 2013-11-30
上傳用戶：wcl168881111111
Learning GNU Emacs 3ed. Emacs和Vi是世界上最好用的編輯器，這本書是Emacs的入門教材。
上傳時間： 2014-11-26
上傳用戶：趙云興
Pascal Programs Printed in GENETIC ALGORITHMS IN SEARCH, OPTIMIZATION, AND MACHINE LEARNING by David E. Goldberg
標簽： OPTIMIZATION ALGORITHMS LEARNING Programs
上傳時間： 2015-04-19
上傳用戶：
這是一個matlab實現(xiàn)第歸神經(jīng)網(wǎng)絡的例子, 實現(xiàn)的第歸神經(jīng)網(wǎng)絡是 : Real Time Recurrent Learning
標簽： Recurrent Learning matlab Real
上傳時間： 2015-04-22
上傳用戶：q123321
LVQ學習矢量化算法源程序 This directory contains code implementing the Learning vector quantization network. Source code may be found in LVQ.CPP. Sample training data is found in LVQ1.PAT. Sample test data is found in LVQTEST1.TST and LVQTEST2.TST. The LVQ program accepts input consisting of vectors and calculates the LVQ network weights. If a test set is specified, the winning neuron (class) for each neuron is identified and the Euclidean distance between the pattern and each neuron is reported. Output is directed to the screen.
標簽： implementing quantization directory Learning
上傳時間： 2015-05-02
上傳用戶：hewenzhi
Learning the bash Shell, 3rd Edition 關于bash Shell介紹的很全面
標簽： Shell bash Learning Edition
上傳時間： 2013-12-15
上傳用戶：koulian
How to Think Like a Computer Scientist Learning with Python 學習linux下Python腳本的必備書籍
標簽： Python Scientist Computer Learning
上傳時間： 2014-10-29
上傳用戶：heart520beat
learning the kalman filter (Matlab Code)
標簽： learning kalman filter Matlab
上傳時間： 2015-06-07
上傳用戶：wab1981
Single-layer neural networks can be trained using various learning algorithms. The best-known algorithms are the Adaline, Perceptron and Backpropagation algorithms for supervised learning. The first two are specific to single-layer neural networks while the third can be generalized to multi-layer perceptrons.
標簽： Single-layer algorithms best-known networks
上傳時間： 2015-06-17
上傳用戶：趙云興
Learning Cpp as a new language.rar
上傳時間： 2015-06-22
上傳用戶：playboys0
