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F# for Machine Learning Essentials by Sudipta Mukherjee

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Understanding logistic regression

Unlike linear regression which is used to predict the real values of a real entity, logistic regression is used to predict the class or tag of an unseen entry. Logistic regression's output is either a 0 or a 1 depicting the predicted class of the unseen entry. Logistic regression uses a smooth curve whose values range from 0 to 1 for all the values of the independent variable.

Sigmoid function (also called logistic function) is one option for this function. This is defined by the following formula:

Understanding logistic regression

The sigmoid function chart

The following chart is generated by the code snippet using FsPlot:

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