12/28/2022 0 Comments Keras one-hot text encoding![]() # Prepare a `tf.data.Dataset` that only yields the feature.įeature_ds = dataset.map(lambda x, y: x) ![]() Index = layers.IntegerLookup(max_tokens=max_tokens) # Otherwise, create a layer that turns integer values into integer indices. Index = layers.StringLookup(max_tokens=max_tokens) # Create a layer that turns strings into integer indices. ![]() def get_category_encoding_layer(name, dataset, dtype, max_tokens=None): See Classify structured data using Keras preprocessing layers for the actual implementation. ![]() I think this way is not plausible in TF 2.4.x so it must have been implemented after. In TF 2.6.0, One Hot Encoding (OHE) or Multi Hot Encoding (MHE) can be implemented using tf., tf., and tf. ![]()
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