python机器学习包mlxtend的安装和配置详解

sudo apt-get install python-matplotlib

sudo apt-get install python-scipy

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
import itertools
from sklearn.linear_model import LogisticRegression
from sklearn.svm import SVC
from sklearn.ensemble import RandomForestClassifier
from mlxtend.classifier import EnsembleVoteClassifier
from mlxtend.data import iris_data
from mlxtend.evaluate import plot_decision_regions

# Initializing Classifiers
clf1 = LogisticRegression(random_state=0)
clf2 = RandomForestClassifier(random_state=0)
clf3 = SVC(random_state=0, probability=True)
eclf = EnsembleVoteClassifier(clfs=[clf1, clf2, clf3], weights=[2, 1, 1], voting='soft')

# Loading some example data
X, y = iris_data()
X = X[:,[0, 2]]

# Plotting Decision Regions
gs = gridspec.GridSpec(2, 2)
fig = plt.figure(figsize=(10, 8))

for clf, lab, grd in zip([clf1, clf2, clf3, eclf],
             ['Logistic Regression', 'Random Forest', 'Naive Bayes', 'Ensemble'],
             itertools.product([0, 1], repeat=2)):
  clf.fit(X, y)
  ax = plt.subplot(gs[grd[0], grd[1]])
  fig = plot_decision_regions(X=X, y=y, clf=clf, legend=2)
  plt.title(lab)
plt.show()

sudo apt-get install python-numpy python-scipy python-matplotlib ipython ipython-notebook python-pandas python-sympy python-nose