KNN.py

weather=['Sunny','Sunny','Overcast','Rainy','Rainy','Rainy','Overcast','Sunny','Sunny', 'Rainy','Sunny','Overcast','Overcast','Rainy'] 
temp=['Hot','Hot','Hot','Mild','Cool','Cool','Cool','Mild','Cool','Mild','Mild','Mild','Hot','Mild'] 
play=['No','No','Yes','Yes','Yes','No','Yes','No','Yes','Yes','Yes','Yes','Yes','No']

from sklearn import preprocessing
le = preprocessing.LabelEncoder()
weather_encoded=le.fit_transform(weather)
temp_encoded=le.fit_transform(temp)
label=le.fit_transform(play)
features=list(zip(weather_encoded,temp_encoded))

from sklearn.neighbors import KNeighborsClassifier
model = KNeighborsClassifier(n_neighbors=3)
model.fit(features,label)

predicted= model.predict([[0,2]])
output=le.inverse_transform(predicted)
print(output)