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1. Evaluating Classification Models: Understanding the Confusion Matrix and ROC Curves

   Learn about the importance of evaluating classification models and how to use the confusion matrix and ROC curves to assess model performance. This post covers the basics of both methods, their components, calculations, and how to visualize the results using Python.

   2024-04-08 Tags: machine learning, classification models, confusion matrix, roc curves, evaluation, true positives, true negatives, false positives, false negatives, accuracy, precision, recall, specificity, f1 score, balanced accuracy by klotz
2. how to compare a classification model to a baseline

   A ready-to-run tutorial in Python and scikit-learn to evaluate a classification model compared to a baseline model

   2024-02-22 Tags: classification, evaluation, baseline, machine learning, roc by klotz
3. More Performance Evaluation Metrics for Classification Problems You Should Know

   2020-04-04 Tags: machine learning, performance, metrics, evaluation by klotz
4. Machine Learning Classifier evaluation using ROC and CAP Curves

   2019-03-11 Tags: machine learning, roc, cap, evaluation by klotz
5. Predicting bankruptcy – Towards Data Science

   2019-02-11 Tags: machine learning, process, evaluation, pca, random forest, bagged dt, bgdt, decision tree by klotz

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