Recap
Explore essential concepts in binary classification using PyTorch, including logistic regression, loss functions, decision thresholds, and evaluation metrics. Learn to prepare data, train models, and analyze performance with tools like ROC and precision-recall curves, gaining a comprehensive understanding to develop practical classification models.
We'll cover the following...
General overview
In this chapter, we have gone through many concepts related to classification problems. This is what we have covered:
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Defining a binary classification problem.
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Generating and preparing a toy dataset using Scikit-Learn’s
make_moonsmethod. -
Defining logits as the result of a linear combination of features.
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Understanding what odds ratios and log odds ratios are.
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Figuring we can interpret logits as log odds ratios.
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Mapping ...