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Set feature importance tensor size according to embedding dimensions (TabNetRegressor) #94

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Set feature importance tensor size according to embedding dimensions (TabNetRegressor) #94

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2 changes: 1 addition & 1 deletion pytorch_tabnet/tab_model.py
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Expand Up @@ -718,7 +718,7 @@ def train_epoch(self, train_loader):
y_preds = []
ys = []
total_loss = 0
feature_importances_ = np.zeros((self.input_dim))
feature_importances_ = np.zeros((self.network.post_embed_dim))

for data, targets in train_loader:
batch_outs = self.train_batch(data, targets)
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