$1.$ Build ML Model using python code for K nearest neighbors, Naive Bayesian, Random Forest, and Adaboost for the below onlineuseradvertisement dataset,

$2.$Performance Evaluation with comments must were Do the prediction for the test data and display the results for the inference. Calculate all the evaluation metrics. Comment on the performance of these models. Answer without comment will not be awarded marks.

$3.$Fine$-$Tuning Hyperparameters. You are required to explore the hyperparameter space for each classifier, utilizing techniques such as grid search or randomized search, to find the optimal combination of parameters that maximizes performance metrics.

$4.$Performance Evaluation: After hyperparameter fine$-$tuning, evaluate the performance of each classifier using the following evaluation measures: Precision, Recall, Accuracy, Misclassification Rate, F Score

$5.$Compare the performance using the evaluation measures and recommend the ML model

Provide with comments over the performance of model before hyper parameter tuning and post hyper parameter tuning

Sample Data set:

Age Gender Income Location Device Interest$\_$Category Time$\_$Spent$\_$on$\_$Site Number$\_$of$\_$Pages$\_$Viewed Click

$056$ Male $99003$ Rural Mobile Sports $81\mathrm{.}9793237270$

$146$ Male $72395$ Suburban Tablet Sports $59\mathrm{.}8540702731$

$232$ Male $59758$ Suburban Tablet Sports $78\mathrm{.}861988820$

$360$ Male $74312$ Urban Tablet Technology $9\mathrm{.}41157880160$

$425$ Female $88670$ Suburban Mobile Fashion $76\mathrm{.}4684086190$

$538$ Female $35434$ Rural Tablet Technology $94\mathrm{.}45593614101$

$656$ Male $84047$ Urban Mobile Sports $62\mathrm{.}5412114441$

$736$ Male $67775$ Rural Mobile Travel $46\mathrm{.}1140327731$

$840$ Male $95769$ Rural Tablet Technology $36\mathrm{.}904074591$

$928$ Male $86677$ Rural Desktop Fashion $78\mathrm{.}92223577171$

$1028$ Male $65734$ Suburban Desktop Sports $84\mathrm{.}67213784140$

$1141$ Female $60603$ Suburban Tablet Technology $105\mathrm{.}161274101$

$1253$ Female $96708$ Rural Tablet Travel $44\mathrm{.}36841948130$

$1357$ Female $88803$ Rural Mobile Technology $93\mathrm{.}52381535120$

$1441$ Female $59332$ Urban Tablet Fashion $69\mathrm{.}5559197810$

$1520$ Male $41312$ Urban Mobile Technology $106\mathrm{.}5261964191$

$1639$ Male $64179$ Suburban Tablet Travel $65\mathrm{.}69839245191$

$1719$ Male $91442$ Suburban Desktop Travel $64\mathrm{.}5274302761$

$1841$ Male $60379$ Urban Desktop Fashion $71\mathrm{.}45586437131$

$1961$ Male $37297$ Rural Tablet Travel $91\mathrm{.}17126584191$

$2047$ Female $22011$ Suburban Mobile Sports $115\mathrm{.}9394051131$