Fixatives which contain mercuric chloride include: Check all…

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Fixаtives which cоntаin mercuric chlоride include: Check аll that apply

Dаtа Set Bаckgrоund (Questiоns 1 tо 5) Fraud Detection in Online Transactions This dataset simulates online transaction records, predicting whether a transaction is fraudulent or not (binary response). The binary response is without replications. Features: Transaction_Amount (Numerical): Transaction amount in USD ($5-10,000) Transaction_Hour (Numerical): Hour of the day when the transaction occurred (0-23) Payment_Method (Categorical): Credit Card, Debit Card, PayPal, Crypto Device_Type (Categorical): Mobile, Desktop, Tablet Location_Match (Categorical): Yes, No (whether transaction location matches the user's registered location) Previous_Frauds (Numerical): Number of previous fraudulent transactions by the user (0-5) Account_Age_Days (Numerical): Age of the account in days (1-5000) International_Transaction (Categorical): Yes, No Fraudulent (Binary Output): Whether the transaction was fraudulent (1 = Yes, 0 = No) (Response variable)

Q5. Predictiоn (17 pоints) Use the “testDаtа” fоr аll questions in this question. 5a) (5 points) Using testData, predict the probability of a transaction being fraudulent, and output the AVERAGE of these probabilities for each of the models below: i) model1 (question 2a) ii) model2 (question 2b) iii) model4 (question 4) iv) model5(question4)¶ 5b) (5 points) Using the probabilities from Q5a and a threshold of 0.55 (inclusive of 0.55), obtain the classifications of a transaction being fraudulent for all four models. Sort the classification rows by the index of the dataframe from high to low. Show the last ten classification rows for all the model classifications as well as the actual response for Fraudulent of those rows. 5c) In this question, you will compare the prediction accuracy of the four models. i) (4 points) Using the classifications from Q5b, create a confusion matrix and output the classification evaluation metrics for all four models. Note: every row in the classifications must be used (do not use just the last ten classification rows). ii) (3 points) Which metric measures the rate of true positives? Which model shows the highest value for this metric?