Execute your code into a jupyter notebook $(.$ipynb file$)$ and keep the output, write a report $(.$pdf file$)$ to answer the following questions, and submit your code and report to OnTrack.

$1.$ Read the article and reproduce the results presented in Table II and Table IV using Python modules 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 $($RSME$,$ and MAE$)$ as shown in Table II and Table IV$.$

$2.$ Design and develop your own ML solution for