Data (A6DATA.csv): https://www.dropbox.com/s/gxa0yf2j7mnp1x4/A6DATA.csv?dl=0

Please note the following:

V1: variance of Wavelet Transformed image (continuous)

V2: skewness of Wavelet Transformed image (continuous)

V3: kurtosis of Wavelet Transformed image (continuous)

V4: entropy of image (continuous)

V5: class (0-forged, 1-genuine)

PART 1:

Read A6DATA.csv file into RStudio.

Run set.seed(222) for partitioning of the dataset into training (50%) and testing (50%).

Please report on the number of forged and genuine banknote-like specimens in the training and testing data.

PART 2:

Develop a logistic regression model using the training data.

Please Provide the final logistic regression model (with only significant variables), equation for calculating probability that specimen is genuine, confusion matrix for both training & testing data, misclassification error for both training & testing data, and please comment on the performance of the model.