Q$2.(15$ pts$)$ Consider a categorical dataset given below.

$\backslash$table$[[$Record#$,$Outlook,Temperature,Humidity,Windy,Play Tennis$],[1,$Rainy,Hot,High,FALSE,No$],[2,$Rainy,Hot,High,TRUE,No$],[3,$Overcast,Hot,High,FALSE,Yes$],[4,$Sunny,Mild,High,FALSE,Yes$],[5,$Sunny,Cool,Normal,FALSE,Yes$],[6,$Sunny,Cool,Normal,TRUE,No$],[7,$Overcast,Cool,Normal,TRUE,Yes$],[8,$Rainy,Mild,High,FALSE,No$],[9,$Rainy,Cool,Normal,FALSE,Yes$],[10,$Sunny,Mild,Normal,FALSE,Yes$],[11,$Rainy,Mild,Normal,TRUE,Yes$],[12,$Overcast,Mild,High,TRUE,Yes$],[13,$Overcast,Hot,Normal,FALSE,Yes$],[14,$Sunny,Mild,High,TRUE,No$]]$

Use the Tanimoto Coefficient$-$based $kNN$ algorithm to predict whether someone would play Tennis or not for the test record given below.

Outlook: Overcast

Temperature: Mild

Humidity: Normal

Windy: False