Patent ID: 9418343
Filing Date: 2016-08-16
CPC Classification: G06N

Claim Text:
1. A computer-implemented method comprising: receiving a first plurality of examples for training a machine learning system, each example having a respective plurality of features, and each example being received at a respective time; obtaining data defining a first point in time; performing a first training iteration by training the machine learning system only on examples having at least one feature initially occurring after the first point in time; obtaining data defining a second point in time occurring subsequent to the first point in time; performing a second training iteration by training the machine learning system only on examples having a feature initially occurring after the second point in time; and performing a third training iteration by training the machine learning system on a second plurality of examples, wherein at least one example of the second plurality has a feature initially occurring after the first point in time, and wherein at least one of the second plurality does not have any features initially occurring after the first point in time.