Find s class Program

Find_S.py

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+import random
+
+attributes = [['Sunny','Rainy'],['Warm','Cold'],['Normal','High'],['Strong','Weak'],['Warm','Cool'],['Same','Change']]
+num_attributes=len(attributes)
+hp = ['$']*num_attributes
+
+
+def getRandomTrainingExample(target_concept=['?']*num_attributes):
+	training_example=[]
+	classification=True
+	for i in range(num_attributes):
+		training_example.append(attributes[i][random.randint(0,1)])
+		if target_concept[i]!='?' and target_concept[i]!=training_example[i]:
+			classification=False
+	return training_example,classification
+
+def findS(training_instance):
+	global hp
+	if training_instance[1]:
+		print "x:\t",training_instance
+		if '$' in hp:
+			hp=training_instance[0]
+		else:
+			for i in range(num_attributes):
+				if hp[i] != training_instance[0][i]:
+					hp[i]='?'
+		print "H:\t",hp,"\n"
+
+
+def main():
+	target_concept=['Sunny','Warm','?','Strong','?','?']
+	num_experiments=50
+	training_examples=[]
+
+	for i in range(num_experiments):
+		training_examples.append(getRandomTrainingExample(target_concept))
+		findS(training_examples[i])
+
+
+
+
+if __name__=="__main__":
+	main()