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The Deep Learning with Keras Workshop
book

The Deep Learning with Keras Workshop

by Matthew Moocarme, Mahla Abdolahnejad, Ritesh Bhagwat
July 2020
Intermediate to advanced content levelIntermediate to advanced
496 pages
9h 10m
English
Packt Publishing
Content preview from The Deep Learning with Keras Workshop

6. Model Evaluation

Overview

This chapter covers model evaluation in depth. We will discuss alternatives to accuracy to evaluate the performance of a model when standard techniques are not feasible, especially where there are imbalanced classes. Finally, we will utilize confusion matrices, sensitivity, specificity, precision, FPR, ROC curves, and AUC scores to evaluate the performance of classifiers. By the end of this chapter, you will have an in-depth understanding of accuracy and null accuracy and will be able to understand and combat the challenges of imbalanced datasets.

Introduction

In the previous chapter, we covered regularization techniques for neural networks. Regularization is an important technique when it comes to combatting ...

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Publisher Resources

ISBN: 9781800562967Supplemental Content