odules and packages $($including your own script or customised codes$).$ Write a report

summarising the dataset, used ML methods, experiment protocol and results including

variations, if any. During reproducing the results:

i$)$ use the same set of features used by the authors.

ii$)$ use the same classifier with exact parameter values.

iii$)$ use the same training$/$test splitting approach as used by the authors.

iv$)$ use the same pre$/$post processing, if any, used by the authors.

v$)$ report the same performance metric $($RMSE$,$ and MAE$)$ as shown in Table II and

Table IV$.$

$2.$ Design and develop your own ML solution for this problem. The proposed solution should

be different from all approaches mentioned in the provided article. This does not mean that

you must have to choose a new ML algorithm.b