According to an embodiment of the present disclosure, a method of training a machine learning model is provided. Input data is received from at least one remote device. A classifier is evaluated by determining a classification accuracy of the input data. A training data matrix of the input data is applied to a selected context autoencoder of a knowledge bank of autoencoders including at least one context autoencoder and the training data matrix is determined to be out of context for the selected autoencoder. The training data matrix is applied to each other context autoencoder of the at least one autoencoder and the training data matrix is determined to be out of context for each other context autoencoder. A new context autoencoder is constructed.
SYSTEM AND METHOD FOR CONTEXT-BASED TRAINING OF A MACHINE LEARNING MODEL
SYSTEM UND VERFAHREN ZUM KONTEXTBASIERTEN TRAINING EINES MASCHINENLERNMODELLS
SYSTÈME ET PROCÉDÉ POUR L'APPRENTISSAGE BASÉ SUR LE CONTEXTE D'UN MODÈLE D'APPRENTISSAGE PAR MACHINE
2020-07-29
Patent
Elektronische Ressource
Englisch
METHOD FOR TRAINING A DEEP-LEARNING-BASED MACHINE LEARNING ALGORITHM
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