Verfahren und System zur Dynamischen Auswahl von Maschinenlernmodellen

Details

Veröffentlichungs-Nr.

EP4811220

Anmeldetag

13. März 2026

Veröffentlichung

23. September 2026

Rechtsraum

EP

Abstract

Conventionally, applications using machine learning models apply same models throughout the working of the application but there is a need to select and switch to appropriate models based on the input data for providing better results. Hence, embodiments of present disclosure provide a method and system for dynamic selection of machine learning models. The method receives input data, extracts features from it and derives a set of parameters from the features. Then, a model fit vector is generated as a weighted combination of the set of parameters. The weights are determined using an entropy-SHAP hybrid technique and further fine-tuned based on a fairness metric. Next, machine learning models are trained using the parameters having weights greater than a threshold value and a model score is calculated for each of the models. Best model is selected based on the model score.

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Firma

Tata Consultancy Services Limited

Land

🇮🇳 Indien