Machine Learning Basics
Some basics of machine learning
2 Bias-Variance
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Category: { Machine Learning } { Basics }
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References:
- Understanding the Bias-Variance Tradeoff
- The Bias-Variance trade-off : Explanation and Demo
- The Element of Statistical Learning
- James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An Introduction to Statistical Learning. In Springer Texts in Statistics. Springer Science & Business Media.
Summary: Bias Variance Trade off is a key concept in statistical learning
Pages: 2
1 Confusion Matrix (Contingency Table)
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Category: { Machine Learning }
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References:
- Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861–874.
- Confusion_matrix#Table_of_confusion @ Wikipedia
- F1 Score
Summary: Confusion Matrix It is much easier to understand the confusion matrix if we use a binary classification problem as an example. For example, we have a bunch of cat photos and the user labeled “cute or not” data. Now we are using the labeled data to train a cute-or-not binary classifier.
Then we apply the classifier on the test dataset and we would only find four different kinds of results.
Pages: 2