Using Multiple Linear regression to solve banknote authentication problem

Aim is to predict whether a given banknote is authentic given a number of measures taken from a photograph.

Data Set used — Banknote Authentication Data Set

A binary classification problem. The dataset consists of 5 columns as follows:

Attributes:

1. Variance of Wavelet Transformed image (continuous).
2. Skewness of Wavelet Transformed image (continuous).
3. Kurtosis of Wavelet Transformed image (continuous).
4. Entropy of image (continuous).

Labels(Target)

5. Output (0 for authentic, 1 for inauthentic).

Result of using the Ordinary Least Squares Regression to fit a linear model-

Partial Regression Plot

Dependence of Misclassification Error on Decision Threshold

Error rate is found to be minimum for a threshold value of 0.67

In-sample ROC for banknote classifier

Out-of-sample ROC for banknote classifier

The entire code can be found on my github profile-

penthaapatel/BankNoteAuthentication