Machine_Learning/candidates_elimination.py at main · 22MH1A42G1/Machine_Learning · GitHub

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#candidates elimination
import pandas as pd
d=pd.DataFrame([['Sunny','Warm','Normal','Strong','Warm','Same','Yes'],
                ['Sunny','Warm','high','Strong','Warm','Same','Yes'],
                ['rainy','cold','high','Strong','Warm','change','no'],
                ['Sunny','Warm','Normal','Strong','cool','change','Yes']])

a=list(d.iloc[:,:-1].values)
b=list(d.iloc[:,-1].values)


s=['@' for i in range(len(a[0]))]
g=[['?' for i in range(len(a[0]))] for j in range(len(a[0]))]

r=0
for i in range(len(b)):
    if b[i]=='Yes' and r==0:
        s=a[i].copy()
        r+=1
        #print(g)
    if b[i]=='Yes' and r>0:
        for j in range(len(s)):
            if s[j]!=a[i][j]:
                s[j]='?'
    if b[i]=='no':
        for k in range(len(g)):
            if s[k]!=a[i][k]:
                g[k][k]=s[k]
            else:
                g[k][k]='?'
print(s)
print(g)
n=[]

for i in range(len(s)):
    if s[i]!=g[i][i]:
        g[i][i]='?'
    if g[i].count('?')!=len(s):
        n.append(g[i])
print(n)