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.
使用神經網絡集成方法診斷糖尿病,肝炎,乳腺癌癥的案例研究.
Windowed-Burg method is made in order to improve the Clasical Burg method. Previously, I send the PBURGW.m file, but now I include also the ARBURGW.m algorithm and some NOTES-EXAMPLES to explain it and compare with the pburg.m algorithm from MATLAB.
For the incomplete methods, we kept the representation of the queens by a table and the method of calculation to determine if two queens are in conflict, which is much faster for this kind of problems than the representation by a matrix.
heuristics: descent.
Tests: 100 queens in less than 1 second and 67 iterations. 500 queens in 1 second and 257 iterations. 1000 queens in 11 seconds and 492 iterations.
heuristics: Simulated annealing.
Tests: 100 queens in less than 1 second and 47 iterations. 500 queens in 5 seconds and 243 iterations. 1000 queens in 13 seconds and 497 iterations.
heuristics: based on Simulated Annealing.
Tests: 100 queens in less than 1 second and 60 iterations. 500 queens in 1 second and 224 iterations. 1000 queens in 5 seconds and 459 iterations. 10 000 queens in 20 minutes 30 seconds and 4885 iterations.
