Machine Learning

Naïve Bayes Classifier - Example -classify- play tennis - forecast Let’s 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. 𝑶𝒖𝒕𝒍𝒐𝒐𝒌 ∈[𝑺𝒖𝒏𝒏𝒚,𝑶𝒗𝒆𝒓𝒄𝒂𝒔𝒕, 𝑹𝒂𝒊𝒏𝒚] 𝑻𝒆𝒎𝒑𝒆𝒓𝒂𝒕𝒖𝒓𝒆∈[𝑯𝒐𝒕,𝑴𝒊𝒍𝒅, 𝑪𝒐𝒐𝒍] 𝑯𝒖𝒎𝒊𝒅𝒊𝒕𝒚 ∈[𝑯𝒊𝒈𝒉, 𝑵𝒐𝒓𝒎𝒂𝒍] 𝑾𝒊𝒏𝒅𝒚 ∈[𝑾𝒆𝒂𝒌, 𝑺𝒕𝒓𝒐𝒏𝒈] The class label is the variable, Play and takes the values Yes or No. 𝑷𝒍𝒂𝒚∈[𝒀𝒆𝒔, 𝑵𝒐] We read-in training data below that has been collected over 14 days Classification Phase Let’s say, we get a new instance of the weather condition ,   𝑿^′=(𝑶𝒖𝒕𝒍𝒐𝒐𝒌=𝑺𝒖𝒏𝒏𝒚, 𝑻𝒆𝒎𝒑𝒆𝒓𝒂𝒕𝒖𝒓𝒆=𝑪𝒐𝒐𝒍, 𝑯𝒖𝒎𝒊𝒅𝒊𝒕𝒚=𝑯𝒊𝒈𝒉, 𝑾𝒊𝒏𝒅