TRAINING RANDOM DECISION TREES FOR SENSOR DATA PROCESSING

A method of training a random decision tree to give improved generalization ability is described. At a split node of the random decision tree a plurality of training sensor data elements available at the split node are divided into a tuning set and a validation set. A plurality of models is formed u...

Ausführliche Beschreibung

Bibliographische Detailangaben

Hauptverfasser:	Le Folgoc, Loïc, Nori, Aditya Vithal, Ancha, Siddharth, Criminisi, Antonio
Format:	Patent
Sprache:	eng
Schlagworte:	CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PHYSICS
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