Create 1.py

Implement and demonstrate the FIND-S algorithm for finding the most specific hypothesis based on a given set of training data samples. Read the training data from a enjoysport.CSV file

Author: fatalcoder524

1.py

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+import csv
+a = []
+with open('enjoysport.csv', 'r') as csvfile:
+    for row in csv.reader(csvfile):
+        a.append(row)
+    print(a)
+print("\n The total number of training instances are : ",len(a))
+num_attribute = len(a[0])-1
+print("\n The initial hypothesis is : ")
+hypothesis = ['0']*num_attribute
+print(hypothesis)
+for i in range(0, len(a)):
+    if a[i][num_attribute] == 'yes':
+        for j in range(0, num_attribute):
+            if hypothesis[j] == '0' or hypothesis[j] == a[i][j]:
+                hypothesis[j] = a[i][j]
+            else:
+                hypothesis[j] = '?'
+    print("\n The hypothesis for the training instance {} is : \n" .format(i+1),hypothesis)
+
+print("\n The Maximally specific hypothesis for the training instance is ")
+print(hypothesis)