Cat-NN for Anomaly Detection

Cat-NN for Anomaly Detection

Cat-NN is a neural network architecture that utilizes categorical features for anomaly detection tasks. This approach improves the model’s ability to detect rare and unusual patterns in data.

By incorporating categorical variables into the neural network, Cat-NN can better identify anomalies in complex datasets, making it a valuable tool for various industries such as finance, cybersecurity, and healthcare.