import numpy as np
from sklearn import datasets
from sklearn import metrics

from matplotlib import pylab as plt

# generate some 2D data set, 2 classes
# check the help for 'datasets.make_classification' function
X, y = datasets.make_classification(1000, n_features=2, weights=[0.4,0.6],
                                    n_informative=2, n_redundant=0, 
                                    n_clusters_per_class=1, flip_y=0.01,
                                    shuffle=True)
                                    
plt.scatter(X[:,0], X[:,1], c=y, cmap=plt.cm.Paired)     

from sklearn.linear_model import Perceptron

# -check the documentation and train/test a model