18CSL76 Implement Candidate-Elimination algorithm

 For a given set of training data examples stored in a . CSV file, implement and demonstrate the Candidate-Elimination algorithm to output a description of the set of all hypotheses consistent with the training examples.

import csv import numpy as np with open('candidate.csv','r') as f: reads=csv.reader(f) tmp_lst=np.array(list(reads)) concept=np.array(tmp_lst[:,:-1]) target=np.array(tmp_lst[:,-1]) for i in range(len(target)): if(target[i]=='yes'): specific_h=concept[i] break h=[] generic_h=[['?' for i in range (len(specific_h))]for i in range (len(specific_h))] print(type(generic_h)) for i in range(len(target)): if(target[i]=='yes'): for j in range (len(specific_h)): if(specific_h[j]!=concept[i][j]): specific_h[j]='?' generic_h[j][j]='?' else: for j in range(len(specific_h)): if(specific_h[j]!=concept[i][j]): generic_h[j][j]=specific_h[j] else: generic_h[j][j]='?' print("Step ",i+1) print("The most generic is : ",generic_h) print("The most specific is : ",specific_h)