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Decode the Classifier’s Answers

Explore how to decode the numerical outputs of a multi-class classifier into human-readable labels. Understand the role of one-hot encoding, matrix dimensions, and numpy functions like argmax in interpreting classifier results. Gain insight into adjusting weight matrices for multi-class problems and verifying matrix multiplication dimensions during training and testing phases.

Overview of classifier

Let’s review how classify() works. During the classification phase, the WSSs return arrays of ten numbers from 00 to 11. But when we ask the system to recognize an image, we do not want to see those arrays, we want a human-readable answer such as “33 ...