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Implementation of AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks

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In your paper, the threshold is set to {10, 5, 10} for Criteo, Avazu and KDD12 And in your code( AutoInt/Dataprocess/Criteo/preprocess.py line.33.36), the threshold is 11 There is nothing wrong...

train according to the procedure: mkdir Criteo python ./Dataprocess/Criteo/preprocess.py python ./Dataprocess/Kfold_split/stratifiedKfold.py python ./Dataprocess/Criteo/scale.py Here's how to run the training. python -u train.py \ --data "Criteo" --blocks 3 --heads 2 --block_shape...

As mentioned in `README.md` https://github.com/shichence/AutoInt/blob/master/README.md#input-format: * train_x: matrix with shape *(num_sample, num_field)*. train_x[s][t] is the feature value of feature field t of sample s in the dataset. The default value...