In [1]:

    

%matplotlib inline
from matplotlib import pylab
import numpy as np


    

In [2]:

    

X1 = np.linspace(0,2,10)
X2 = X1*np.random.rand(10)

X3 = np.linspace(4,6,10)
X4 = X3*np.random.rand(10)
a = np.ones(10)*3


    

In [3]:

    

pylab.scatter(X1,X2, color="b", marker="o", label="Neg")
pylab.scatter(X3,X4, color="r", marker="x", label="Pos")
pylab.plot(a,np.arange(-1,9),label="Decision Boundary")
pylab.xlabel("feature X1")
pylab.ylabel("feature X2")
pylab.legend(loc="upper right", bbox_to_anchor=(1.5,1))
pylab.show()


    

    




/home/bharat/anaconda2/lib/python2.7/site-packages/matplotlib/collections.py:590: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison
  if self._edgecolors == str('face'):






    

In [4]:

    

z = np.linspace(-5,5)


    

In [5]:

    

def sigmoid(x):
    return 1./(1. + np.exp(-x))


    

In [6]:

    

pylab.plot(z,sigmoid(z),label="Sigmoid Curve")
pylab.xlabel("Distance of point from Decision Boundary")
pylab.ylabel("P(X)")
pylab.legend(loc="best")
pylab.show()