Lab 1

 Import pandas as pd

Import numpy as np


#to read the data in the csv file

Data = pd.read_csv(“data.csv”)

Print(data,”n”)


#making an array of all the attributes

D = np.array(data)[:,:-1]

Print(“n The attributes are: “,d)


#segragating the target that has positive and negative examples

Target = np.array(data)[:,-1]

Print(“n The target is: “,target)


#training function to implement find-s algorithm

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

#obtaining the final hypothesis

Print(“n The final hypothesis is:”,train(d,target))

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