Model Evaluation

Model Evaluation for Data Science Algorithms

1. Regression

Regression falls under Supervised learning where output variable is a continuous variable. Let’s explore model evaluation metrics used in regression.

R-Square MAE MSE RMSE

2. Classification

Classification models falls under Supervised learning where output variable is a categorical variable. Below are the evaluation metrics used in classification algorithms.

Confusion Matrix AUC-ROC Gain Chart Lift Chart KS Statistic

3. Clustering

Clustering models falls under unsupervised learning. There are no labels in clustering. Models are evaluated based on some similarity or dissimilarity measure such as the distance between cluster points.

Silhouette Coefficient Dunn’s Index

Keytodatascience Logo

Connect

Subscribe

Join our email list to receive the latest updates.

© 2022 KeyToDataScience