Logistic regression: basic concepts
Logistic regression is a method used for binary classification tasks, predicting the probability of an instance belonging to a one of two classes (typically 0 or 1). It employs a logistic (sigmoid) function to transform a linear combination of input features and parameters into a probability score between 0 and 1. The model then classifies instances based on a chosen threshold: it will offer a prediction of 1 if the model output is over the threshold and a prediction of 0 if the model output is under the threshold.
Coding assignments: https://github.com/ionpetre/FoundML_c...
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