A Naive Bayes Classifier created to predict the chances of playing tennis based on the weather and temperature conditions.
It is a simple and most effective classification algorithm which is a probabilistic classifier. It makes predictions on the basis of probability of an object.
This classifier was created to predict the chances of playing tennis on a specific day based on the different weather and temperature conditions. The model predicts that the there is 81% chances of not being able to play tennis.
The datasets defined for the model:
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']