Banknote Authentication
Banknote Authentication Data Science Project
Classification in Depth with Scikit-Learn

Banknote Authentication

For this project, you will practice with a given a banking dataset related to direct marketing campaigns of a Portuguese banking institution. Using an XGBoost classifier to will try to predict which clients are more likely to subscribe for a long-term deposit, so that the bank can focus its marketing efforts on such clients.
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Project Activities

All our Data Science projects include bite-sized activities to test your knowledge and practice in an environment with constant feedback.

All our activities include solutions with explanations on how they work and why we chose them.

multiplechoice

The Banknote Authentication dataset consists of images of genuine and forged banknotes. True or False ?

multiplechoice

SVMs are not affected by the scale of the input features. True or False ?

multiplechoice

Based on the GridSearchCV result using C= [0.1, 1, 10, 100,1000], Which is the value of C for the SVM classifier that present the best score?

codevalidated

Check the predictions of the test dataset using the best models obtained from GridSearchCV.

Store the model in the variable grid.

Banknote AuthenticationBanknote Authentication
Author

Verónica Barraza

This project is part of

Classification in Depth with Scikit-Learn

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