Question

Create a Decision tree classifier in sci-kit learn using the Data given below,
features = [[2,100],[6,25],[1,300],[1,1000],[4,100],[10,100]]
Label = [1,2,1,1,2,2]
Note : 1 - Sports/Race Car and 2 - Family Car​

Answer 1

Answer:

from sklearn.tree import DecisionTreeClassifier

feature=[[2,100],[6,25],[1,300],[1,1000],[4,100],[10,100]]

Label=[1,2,1,1,2,2]

clf=DecisionTreeClassifier(random_state=0)

clf.fit(features,Label)

x1,x2=input().split()

print(clf.predict([[x1,x2]]))