Question: The answers to this problem are based on R version 3 . 5 . 3 . To replicate the results with newer versions of R
The answers to this problem are based on R version To replicate the results with newer versions of R execute the following line of code at the beginning of the R session or your R code: suppressWarningsRNGversion For R partition data sets into training and validation. Use the statement set.seed to specify the random seed of for both data partitioning and crossvalidation. If the predictor variable values are in the character format, then treat the predictor variable as a categorical variable. Otherwise, treat the predictor variable as a numerical variable. Credit card fraud is becoming a serious problem for the financial industry and can pose a considerable cost to banks, credit card issuers, and consumers. Fraud detection using data mining techniques has become an indispensable tool for banks and credit card companies to combat fraudulent transactions. The accompanying data file contains the following variables: Fraud if fraudulent activities, otherwise Amount if low, if medium, if high Online if online transactions, otherwise and Prior if products that the card holder previously purchased, otherwise APartition the data to develop a nave Bayes classification model. Report the accuracy, sensitivity and specificity rates for the validation data set. Note: Round your answers to decimal places. bWhat is the lift value of the leftmost bar? cWhat is the area under the ROC curve or AUC value dWhich of the following statements is most accurate? aBy selecting the top of the validation cases with the highest predicted probability of belonging to the target class, the nave Bayes model would identify more target class cases than if the cases are randomly selected. bUsing as the cutoff rate, the nave Bayes models accuracy rate is higher than that of the nave rule classifying all cases to the predominant class for the validation data. C The lift curve of the nave Bayes model lies slightly above the lift curve of the baseline model. D Overall, the nave Bayes model performs better than the baseline model in terms of both sensitivity and specificity. E All of the statements above are accurate Change the cutoff value to Report the accuracy, sensitivity specificity, and precision rates for the validation data set. Note: Round your answers to decimal places. table msodisplayeddecimalseparator:"; msodisplayedthousandseparator:"; tr msoheightsource:auto; col msowidthsource:auto; td paddingtop:px; paddingright:px; paddingleft:px; msoignore:padding; color:black; fontsize:pt; fontweight:; fontstyle:normal; textdecoration:none; fontfamily:Calibri, sansserif; msofontcharset:; textalign:general; verticalalign:bottom; border:none; whitespace:nowrap; msorotate:;xltextalign:right; Fraud Amount Online Prior
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