Exercise LFD and PLA (Perceptron learning Algorithm)

lfd_pla.py

import matplotlib.pyplot as plt
import numpy as np
import scipy as sp
import os
from sklearn.linear_model import LogisticRegression
from six.moves import cPickle as pickle
from sklearn.datasets import load_iris

%matplotlib inline


def randomize(dataset, labels):
  permutation = np.random.permutation(labels.shape[0])
  shuffled_dataset = dataset[permutation]
  shuffled_labels = labels[permutation]
  print(permutation.shape, len(permutation))
  return shuffled_dataset, shuffled_labels


def randomize_in_place(list1,list2, init):
    np.random.seed(seed=init)
    np.random.shuffle(list1)
    np.random.seed(seed=init)
    np.random.shuffle(list2)
        

def sign(x):
    if x<0:
        return -1
    else:
        return +1
        
def h(theta,x):
    return sign(theta.dot(x))

def diffe(w,vX,vy):
    l = []
    for i,e in enumerate(vX):
        if h(w,e)!=vy[i]:
            l.append([e,vy[i]])
    return l


def draw_line(w,vX):
    if w[2]==0:
        print("not defined")
        return vX*0
    else:
        return (vX*-w[1])/w[2] -(w[0]/w[2])

        
W = np.random.random(50,)*-25 +29
Z = np.random.random(50,)*246 +45
R = np.random.random(50,)*-19 -22
S = np.random.random(50,)*177 -90
points1 = [[i,e] for i,e in zip(W,Z)]
points2 = [[i,e] for i,e in zip(R,S)]
qX = np.array(points1 + points2)
X = np.array(np.insert(qX, 0, 1, axis=1))
y = np.array([1]*50 +[-1]*50)

randomize_in_place(X,y,0)

#              B x1 x2
wg = np.array([-40,9,1])

grafX = np.arange(-100,100,0.1)
grafY = draw_line(wg,grafX)
plt.plot(grafX,grafY,W,Z,'o',R,S,'x')
plt.show()
print(len(diffe(wg,X,y)))

#              B x1 x2
w0 = np.array([20,3.4,1])
grafY = draw_line(w0,grafX)
plt.plot(grafX,grafY,W,Z,'o',R,S,'x')
plt.show()
print(len(diffe(w0,X,y)))

#              B x1 x2
w1 = np.array([0,0,0])
grafY = draw_line(w1,grafX)
plt.plot(grafX,grafY,W,Z,'o',R,S,'x')
plt.show()


def PLA(w,vX,vy):
    while diffe(w,vX,vy)!=[]:
        w = w + (diffe(w,vX,vy)[0][1])*(diffe(w,vX,vy)[0][0])
        grafY = draw_line(w,grafX)
        plt.plot(grafX,grafY,W,Z,'o',R,S,'x')
        plt.show()
    return w

print(PLA(w1,X,y))