How to Implement Logistic Regression Algorithm, with Orange Data Science Tool

A Classification problem, we implemented the Logistic Regression solution with the Orange Data Science tool

Logistic regression is another technique borrowed by machine learning from the field of statistics.

It is the go-to method for binary classification problems (problems with two class values). In this post you will discover the logistic regression algorithm for machine learning.

After reading this post you will know:

• The many names and terms used when describing logistic regression (like log odds and logit).
• The representation used for a logistic regression model.
• Techniques used to learn the coefficients of a logistic regression model from data.
• How to actually make predictions using a learned logistic regression model.
• Where to go for more information if you want to dig a little deeper.

This post was written for developers interested in applied machine learning, specifically predictive modeling. You do not need to have a background in linear algebra or statistics.

Concepts of Regression Logistic

Now Implement Logistic Regression with Orange Tools

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