import pandas as pd
import numpy as np
data=pd.read_csv(“/home/user/Downloads/data.csv”)
print(data,”\n”)
d=np.array(data)[:,:-1]
print(“\nThe attributes are:”,d)
target=np.array(data)[:,-1]
print(“\nThe target is:”,target)
def train(c,t):
for i,val in enumerate(t):
if val==”Yes”:
specific_hypothesis=c[i].copy()
break;
for i,val in enumerate(c):
if t[i]==”Yes”:
for x in range(len(specific_hypothesis)):
if val[x]!=specific_hypothesis[x]:
specific_hypothesis[x]=’?’
else:
pass
return specific_hypothesis
print(“\nFinal Hypothesis is:”,train(d,target))import pandas as pd
import numpy as np
data=pd.read_csv(“/home/user/Downloads/data.csv”)
print(data,”\n”)
d=np.array(data)[:,:-1]
print(“\nThe attributes are:”,d)
target=np.array(data)[:,-1]
print(“\nThe target is:”,target)
def train(c,t):
for i,val in enumerate(t):
if val==”Yes”:
specific_hypothesis=c[i].copy()
break;
for i,val in enumerate(c):
if t[i]==”Yes”:
for x in range(len(specific_hypothesis)):
if val[x]!=specific_hypothesis[x]:
specific_hypothesis[x]=’?’
else:
pass
return specific_hypothesis
print(“\nFinal Hypothesis is:”,train(d,target))