https://documentation.opengate.es/api/artificial_intelligence/training_plans/index.html The catalogue of ready-made training recipes a trainer can run: what a plan declares — algorithm, data source types, configuration fields, expected columns, minimum data and container image — how to list them, and the plans available today. Hugo en-us https://documentation.opengate.es/api/artificial_intelligence/training_plans/radius_isolation_forest/index.html Mon, 01 Jan 0001 00:00:00 +0000 https://documentation.opengate.es/api/artificial_intelligence/training_plans/radius_isolation_forest/index.html Learns what a normal data session looks like on one APN and flags the sessions that do not fit: the data it needs, how it trains, the prediction request and answer, and the rule and alarm it creates. https://documentation.opengate.es/api/artificial_intelligence/training_plans/radius_autoencoder/index.html Mon, 01 Jan 0001 00:00:00 +0000 https://documentation.opengate.es/api/artificial_intelligence/training_plans/radius_autoencoder/index.html The same RADIUS-per-APN problem solved with a neural network that learns to reconstruct normal sessions and flags the ones it reconstructs badly: data, training, prediction contract and the rule it creates. https://documentation.opengate.es/api/artificial_intelligence/training_plans/image_anomaly_detection/index.html Mon, 01 Jan 0001 00:00:00 +0000 https://documentation.opengate.es/api/artificial_intelligence/training_plans/image_anomaly_detection/index.html Tells defective items from correct ones in photographs and draws a heat map of the defect: the folders of images it trains on, the two models it combines, the prediction request over the organization's file space, and the rule and alarm it creates.