Breaking Down Classification Evaluation Metrics

Accuracy, Precision, Recall, ROC Curve, True Positive, False Positive, True Negative, and False Negative

The classification problem is a data mining task where the ultimate goal is to accurately predict the categorical response variable. The setup often requires a training data containing a set of attributes and the target and a prediction set for which the algorithm is given a data not seen before. Then, the algorithm analyses the input and generates the prediction output (see…

Keep the story going. Sign up for an extra free read.

You've completed your member preview for this month, but when you sign up for a free Medium account, you get one more story.
Already have an account? Sign in

Korkrid Kyle Akepanidtaworn

Written by

Cloud Solution Architect (Data & AI) at Microsoft, Former Data Scientist at Accenture Applied Intelligence

Welcome to a place where words matter. On Medium, smart voices and original ideas take center stage - with no ads in sight. Watch
Follow all the topics you care about, and we’ll deliver the best stories for you to your homepage and inbox. Explore
Get unlimited access to the best stories on Medium — and support writers while you’re at it. Just $5/month. Upgrade