Data Science from Scratch with Python: Concepts and Practices with NumPy, Pandas, Matplotlib, Scikit-Learn and Keras by Publishing AI

Author:Publishing, AI [Publishing, AI]
Language: eng
Format: epub
Publisher: AI Publishing LLC
Published: 2019-08-11T16:00:00+00:00

Our data can now be trained using a logistic regression model.

We test our model and get 77% which is not that good. However, you can do the same steps with the normalization and see how this score drops dramatically.

Following that, we plot our features against their model weights using a bar plot to see if the model is getting more complex than needed, and thus, can be prone to overfitting.

Now let us use L1 regularization. As we see, the accuracy decreases by nearly 1.5% but the weights of the model are now much smaller, so we do not have to worry about overfitting.

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