$1.$ Download the DryBean dataset. The dataset contains $13611$ instances, $16$ descriptive features,

and the class feature Class in column Q$.$

$2.$ You now have to very carefully explore the dataset to identify any issues with in this dataset. Identify the issues and explain how you have addressed these issues.

$3.$ Decide on the bagging and boosting ensemble learning model that you will use. Give justications for why you have selected these ensemble learning models.

$4.$ Discuss the data$-$preprocessing steps that you have implemented to optimally transform the dataset for the chosen ensemble learning approaches. Note: do not do unnecessary data transformations. Carefully think about the data transformations needed for the selected ensemble learning approach. Provide justications for each of these pre$-$processing steps. Should you decide not to address a data quality issue, justify this decision.