Logistic Regression
📘 Artificial Intelligence & Machine Learning Basics
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📅 Nov 05, 2025
⏱ Estimated reading time: 1 min
Definition:
A supervised learning algorithm used for classification problems, predicting the probability of a categorical outcome.
Key Points:
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Predicts 0 or 1 (binary) or multiple classes
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Uses sigmoid function: σ(z)=1+e−z1
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Threshold (usually 0.5) decides the class
Applications:
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Spam detection
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Credit approval
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Disease diagnosis
Advantages:
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Simple, interpretable
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Outputs probabilities
Limitations:
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Not suitable for complex/non-linear relationships
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