mulefish/simple_classifiers

Naive Bayes Node

simple_classifiers

Naive Bayes Node

Toy dataset:

Outlook,Temperature,Humidity,Windy,Play Rainy,Hot,High,False,No Rainy,Hot,High,True,No Overcast,Hot,High,False,Yes Sunny,Mild,High,False,Yes Sunny,Cool,Normal,False,Yes Sunny,Cool,Normal,True,No Overcast,Cool,Normal,True,Yes Rainy,Mild,High,False,No Rainy,Cool,Normal,False,Yes Sunny,Mild,Normal,False,Yes Rainy,Mild,Normal,True,Yes Overcast,Mild,High,True,Yes Overcast,Hot,Normal,False,Yes Sunny,Mild,High,True,No The first 4 columns are 'dependent features' and the 'Play' column is the 'response vector' ( i.e., it is the prediction )

Assumption

The fundamental Naive Bayes assumption is that each feature makes an is INDEPENDENT and EQUAL in weight

Formula

                {P(B|A) P(A)}     
 P(A|B) =   ______________________  
                    {P(B)}   

url

A nice description + the data for the tests herein:
https://www.geeksforgeeks.org/naive-bayes-classifiers/