Algorithm-specific neural network architectures for automatic machine learning model selection
Номер патента: EP3688680A1
Опубликовано: 05-08-2020
Автор(ы): Nipun Agarwal, Sam Idicula, Sandeep Agrawal, Venkatanathan Varadarajan
Принадлежит: Oracle International Corp
Опубликовано: 05-08-2020
Автор(ы): Nipun Agarwal, Sam Idicula, Sandeep Agrawal, Venkatanathan Varadarajan
Принадлежит: Oracle International Corp
Реферат: Techniques are provided for selection of machine learning algorithms based on performance predictions by trained algorithm-specific regressors. In an embodiment, a computer derives meta-feature values from an inference dataset by, for each meta-feature, deriving a respective meta-feature value from the inference dataset. For each trainable algorithm and each regression meta-model that is respectively associated with the algorithm, a respective score is calculated by invoking the meta-model based on at least one of: a respective subset of meta-feature values, and/or hyperparameter values of a respective subset of hyperparameters of the algorithm. The algorithm(s) are selected based on the respective scores. Based on the inference dataset, the selected algorithm(s) may be invoked to obtain a result. In an embodiment, the trained regressors are distinctly configured artificial neural networks. In an embodiment, the trained regressors are contained within algorithm-specific ensembles. Techniques are also provided for optimal training of regressors and/or ensembles.
Algorithm-specific neural network architectures for automatic machine learning model selection
Номер патента: WO2019067957A1. Автор: Nipun Agarwal,Sam Idicula,Sandeep Agrawal,Venkatanathan Varadarajan. Владелец: ORACLE INTERNATIONAL CORPORATION. Дата публикации: 2019-04-04.