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One hot encode function (for model-building, keras, etc)

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Aabehmiel
Last edited Aug 3, 2017
Created on Aug 3, 2017

This example demonstrates a one-hot encoding function that converts an array of categorical object labels into a binary matrix format suitable for training neural networks in Keras. The code defines `one_hot_encode_object_array`, which uses NumPy’s `np.unique` with `return_inverse=True` to map each unique string to an integer ID, then passes those IDs to `np_utils.to_categorical` from Keras to produce the final encoded vectors. It applies this transformation separately to training and testing label arrays (`train_y` and `test_y`), storing the results as `train_y_ohe` and `test_y_ohe` for subsequent model building.

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