Witam,
mam program w pythonie. Niestety nie chce on mi się uruchomić poprawnie. Wyrzuca błąd modułu pcn.
Skąd można ściągnąć ten moduł pod system 64 bit?
Pozdrawiam
Źródło:
# Code from Chapter 2 of Machine Learning: An Algorithmic Perspective
# by Stephen Marsland (http://seat.massey.ac.nz/personal/s.r.marsland/MLBook.html)
# You are free to use, change, or redistribute the code in any way you wish for
# non-commercial purposes, but please maintain the name of the original author.
# This code comes with no warranty of any kind.
# Stephen Marsland, 2008
# Demonstration of the Perceptron on the Pima Indian dataset
from pylab import *
from numpy import *
import pcn
pima = loadtxt('/pima.data',delimiter=',')
# Plot the first and second values for the two classes
#indices0 = where(pima[:,8]==0)
#indices1 = where(pima[:,8]==1)
#
#ion()
#plot(pima[indices0,0],pima[indices0,1],'go')
#plot(pima[indices1,0],pima[indices1,1],'rx')
# Perceptron training on the original dataset
print "Output on original data"
p = pcn.pcn(pima[:,:8],pima[:,8:9])
p.pcntrain(pima[:,:8],pima[:,8:9],0.25,100)
p.confmat(pima[:,:8],pima[:,8:9])
# Various preprocessing steps
pima[where(pima[:,0]>8),0] = 8
pima[where(pima[:,7]<=30),7] = 1
pima[where((pima[:,7]>30) & (pima[:,7]<=40)),7] = 2
pima[where((pima[:,7]>40) & (pima[:,7]<=50)),7] = 3
pima[where((pima[:,7]>50) & (pima[:,7]<=60)),7] = 4
pima[where(pima[:,7]>60)] = 5
pima[:,:8] = pima[:,:8]-pima[:,:8].mean(axis=0)
pima[:,:8] = pima[:,:8]/pima[:,:8].var(axis=0)
#print pima.mean(axis=0)
#print pima.var(axis=0)
#print pima.max(axis=0)
#print pima.min(axis=0)
trainin = pima[::2,:8]
testin = pima[1::2,:8]
traintgt = pima[::2,8:9]
testtgt = pima[1::2,8:9]
# Perceptron training on the preprocessed dataset
print "Output after preprocessing of data"
p1 = pcn.pcn(trainin,traintgt)
p1.pcntrain(trainin,traintgt,0.25,100)
p1.confmat(testin,testtgt)
show()
Plik pima.data
6,148,72,35,0,33.6,0.627,50,1
1,85,66,29,0,26.6,0.351,31,0
8,183,64,0,0,23.3,0.672,32,1
1,89,66,23,94,28.1,8.167,21,0
2,197,70,45,543,30.5,0.158,53,1
8,125,96,0,0,0.0,0.232,54,1
4,110,92,0,0,37.6,0.191,30,0
10,168,74,0,0,38.0,0.537,34,1