Task $3$:

$3\mathrm{.}1$ Fit a random forest model on $$Train$.$csv$$ with a random state of $1,500$ epochs, a maximum depth of $3$ and a maximum feature of $3.$

$3\mathrm{.}2$ Evaluate the confusion matrix, F$1$ scores and accuracy. Compare the random forest model with the logistic regression. State your observations in a markdown cell in your Jupyter notebook.

Task $4$:

$4\mathrm{.}1$ Fit support vector machine $($SVM$)$ algorithms on $$Train$.$csv$$ with the following parameters: gamma $=0\mathrm{.}025$ ; C$=3.$

$4\mathrm{.}2$ Provide the confusion matrix, F$1$ scores and accuracy in a markdown cell in your Jupyter notebook.

Task $5$:

$5\mathrm{.}1$ Fit an ANN model $($sequential$)$ with $16$ input neurons and add two hidden layers with $8$ neurons each.

$5\mathrm{.}2$ Use $$relu$$ activation and adam optimiser. Use the normal kernel initialiser. Run it for $100$ epochs on $$train$.$csv$$ with a batch size of $15.$

$5\mathrm{.}3$ Provide the confusion matrix, F$1$ scores and accuracy on the test dataset in a markdown cell in your Jupyter notebook.

Task $6$:

Explain which model you will use based on the evaluation metrics on the test dataset among all the models $($logistic regression, random forest, SVM and ANN$)$ and explain why. Put your answer in a markdown cell in your Jupyter notebook.

ID A numerical value assigned to each credit card customer

LIMIT$\_$BAL The remaining credit a customer can use

SEX $1=$ male ; $2=$ female

EDUCATION $1=$ graduate school ; $2=$ university ; $3=$ high school ; $4=$ others ; $5=$ unknown ; $6=$ unknown

MARRIAGE $0=$ unknown $1=$ married $2=$ single $3=$ others

AGE A customer$$s age in years

PAY$\_0$ Repayment status in September $2005$: $0$ or less: Paid duly ; $1$ or greater $=$ payment was delayed

PAY$\_2$ Repayment status in August $20050$ or less: Paid duly ; $1$ or greater $=$ payment was delayed

PAY$\_3$ Repayment status in July $20050$ or less: Paid duly ; $1$ or greater $=$ payment was delayed

PAY$\_4$ Repayment status in June $20050$ or less: Paid duly ; $1$ or greater $=$ payment was delayed

PAY$\_5$ Repayment status in May $20050$ or less: Paid duly ; $1$ or greater $=$ payment was delayed

PAY$\_6$ Repayment status in April $20050$ or less: Paid duly ; $1$ or greater $=$ payment was delayed

BILL$\_$AMT$1$ The amount in the bill statement for September $2005$ in NT dollar

BILL$\_$AMT$2$ The amount in the bill statement for August $2005$ in NT dollar

BILL$\_$AMT$3$ The amount in the bill statement for July $2005$ in NT dollar

BILL$\_$AMT$4$ The amount in the bill statement for June $2005$ in NT dollar

BILL$\_$AMT$5$ The amount in the bill statement for May $2005$ in NT dollar

BILL$\_$AMT$6$ The amount in the bill statement for April $2005$ in NT dollar

PAY$\_$AMT$1$ The amount paid in NT dollar in September $2005$

PAY$\_$AMT$2$ The amount paid in NT dollar in August $2005$

PAY$\_$AMT$3$ The amount paid in NT dollar in July $2005$

PAY$\_$AMT$4$ The amount paid in NT dollar in June $2005$

PAY$\_$AMT$5$ The amount paid in NT dollar in May $2005$

PAY$\_$AMT$6$ The amount paid in NT dollar in April $2005$

Default Shows customers who defaulted on their payments on the following month: $1=$ yes $0=$ no