From the course: Machine Learning with Scikit-Learn

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Logistic regression using scikit-learn

Logistic regression using scikit-learn - scikit-learn Tutorial

From the course: Machine Learning with Scikit-Learn

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Logistic regression using scikit-learn

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- [Instructor] How do you create a logistic regression model using scikit-learn? The first thing that you need to know is that despite the name logistic regression contain the word regression, logistic regression is actually a model user classification. Classification models can be used for tasks like classifying flower species or image recognition. All of this of course depends on the availability and quality of your data. Logistic regression has some advantages, model training and predictions are relatively fast, additionally, no tuning is usually needed for the model. Finally, it can perform well with a small number of observations. In this video, I'll share with you how you can create a logistic regression model for binary classification. The first thing that you need to do is import the libraries that you want to use. In this notebook, it's Matplotlib, numpy, seaborn, pandas, as well as train_test_split,…

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