The complete this Assignment:

Unzip the Wk$8$Assignment$\_$DataAndProcess zip file in a directory of your choice to retrieve the following files:

$05\_$Regression$\_5\mathrm{.}2\_$logreg$\_$credit$\_$scores.csv

$05\_$Regression$\_5\mathrm{.}2\_$LogReg$\_2$attr$\_$cred$\_$scoring.rmp

Create a RapidMiner repository called W$8$ to hold your work for this Assignment. Create two subfolders $($data and processes$)$ under the W$8$ repository.

Import both the data set and the RapidMiner process into their respective subfolders of your W$8$ repository. Your Design view should look like this: A$8-$Step$3.$jpg

Prepare the data set and run the $05\_$Regression$\_5\mathrm{.}2\_$LogReg$\_2$attr$\_$cred$\_$scoring RapidMiner process. Examine the resulting confusion matrix in the Results view and notice that class recall performance of the model is $71\mathrm{.}43\%($positive class: Y$).$

Modify the $05\_$Regression$\_5\mathrm{.}2\_$LogReg$\_2$attr$\_$cred$\_$scoring RapidMiner process and its operators to increase the class recall performance to $80\%.$

Take screenshots of the results of your work.

Explain your work, interpret your results, and reflect on your experience:

Explain how you prepared the data set and how you modified the RapidMiner process to increase the class recall performance to $80\%.$

Interpret the results of your prediction model $($the recall performance metrics and the reason for wanting to increase it$).$

Reflect on your experience with this task and lessons learned.

Prepare your deliverables as follows:

Prepare all the required screenshots.

Prepare all your explanations, interpretations, and reflections.

Zip your entire W$8$ repository.

Complete all four sections $($copy of repository and screenshots; explanation of work; interpretation of results; and reflection$)$ of the Solution Submission Template, as directed in the template.