10_Scoring
This directory contains 6 workflows.
01_Evaluating_Classification_Model_Performance
This workflow trains a classification model using the Decision Tree algorithm and evaluates its accuracy by scoring metrics, ROC Curve, and Lift […]
03_Adjusting_Class_Probabilities_after_Resampling
This workflow compares the performances of three different setups for a classification model that is used to detect fraud in credit card data. Scenario 1: […]
04_Evaluating_Regression_Model_Performance
This workflow trains a linear regression model that predicts the amount of a credit. The performance of the linear regression model is evaluated with the […]
05_Cohen's_Kappa_for_Evaluating_Classification_Models
This workflow demonstrates how Cohen's kappa can be used to evaluate the performance of a classification model when dealing with imbalanced data. We also […]
06_Assessing_Effects_of_Single_Predictors_with_Delta-p
This workflow calculates the Delta-p statistics based on the coefficient statistics of a logistic regression model. The Delta-p statistics tells the effect […]
07_Visual_Scoring_Techniques_for_Classification_Models
This workflow implements the following visual model scoring techniques: - ROC Curve - Lift Chart - Cumulative Gain Chart In addition, the Binary […]