Naive Bayes Classifier - Example -classify- play tennis - forecast
NaΓ―ve Bayes Classifier - Example -classify- play tennis - forecast Letβs build a classifier that predicts whether I should play tennis given the forecast . It takes four attributes to describe the forecast; namely, the outlook , the temperature , the humidity , and the presence or absence of wind . Furthermore, the values of the four attributes are qualitative (also known as categorical ). They take on the values shown below. πΆππππππ β[πΊππππ,πΆπππππππ, πΉππππ] π»ππππππππππβ[π―ππ,π΄πππ
, πͺπππ] π―ππππ
πππ β[π―πππ, π΅πππππ] πΎπππ
π β[πΎπππ, πΊπππππ] The class label is the variable, Play and takes the values Yes or No. π·πππβ[πππ, π΅π] We read-in training data below that has been collected over 14 days Classification Phase Letβs say, we get a new instance of the weather condition , πΏ^β²=(πΆππππππ=πΊππππ, π»ππππππππππ=?...