keras

Neural network balanced weight for imbalanced classification

Neural Network Model Balanced Weight For Imbalanced Classification In Keras

When using a neural network model to classify imbalanced data, we can adjust the balanced weight for the cost function to give more attention to the minority class. Python’s Keras library has a built-in option called class_weight to help us achieve this quickly. One benefit of using the balanced weight adjustment is that we can use the …

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Autoencoder For Anomaly Detection Using Tensorflow Keras

Autoencoder For Anomaly Detection Using Tensorflow Keras

Autoencoder is an unsupervised neural network model that uses reconstruction error to detect anomalies or outliers. The reconstruction error is the difference between the reconstructed data and the input data. Autoencoder uses only normal data to train the model and all data to make predictions. Therefore, we expect outliers to have higher reconstruction errors because …

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