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Showing posts from February, 2020

Handling imbalanced classes, up-sampling, down-sampling, performance metric, penalize algorithm, tree-based algorithm, SMOTE algorithm

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mbalanced classes put “accuracy” out of business. This is a surprisingly common problem in machine learning (specifically in classification), occurring in datasets with a disproportionate ratio of observations in each class. Standard accuracy no longer reliably measures performance, which makes model training much trickier. Imbalanced classes appear in many domains, including: Free: Data Science Career Guide Learn how to  land a  high-paying job in data science  and  future-proof your career  with the most efficient  roadmap   to learning DS & ML for busy professionals. Send My Download Fraud detection Spam filtering Disease screening SaaS subscription churn Advertising click-throughs In this guide, we’ll explore 5 effective ways to handle imbalanced classes. Intuition: Disease Screening Example ...