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Applied Supervised Learning with Python

You're reading from  Applied Supervised Learning with Python

Product type Book
Published in Apr 2019
Publisher
ISBN-13 9781789954920
Pages 404 pages
Edition 1st Edition
Languages
Authors (2):
Benjamin Johnston Benjamin Johnston
Profile icon Benjamin Johnston
Ishita Mathur Ishita Mathur
Profile icon Ishita Mathur
View More author details

Logistic Regression


The logistic or logit model is one such non-linear model that has been effectively used for classification tasks in a number of different domains. In this section, we will use it to classify images of hand-written digits. In understanding the logistic model, we also take an important step in understanding the operation of a particularly powerful machine learning model, artificial neural networks. So, what exactly is the logistic model? Like the linear model, which is composed of a linear or straight-line function, the logistic model is composed of the standard logistic function, which, in mathematical terms, looks something like this:

Figure 4.8: Logistic function

In practical terms, when trained, this function returns the probability of the input information belonging to a particular class or group.

Say we would like to predict whether a single entry of data belongs to one of two groups. As in the previous example, in linear regression, this would equate to y being either...

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