Patent ID: 11869021
Assignee: ADOBE INC.
Field: IT methods for management (Electrical engineering)
Classification: CPC G | IPC G

Claim 9:
10. One or more computer readable storage media having stored instructions that, responsive to execution by a processing system, causes the processing system to perform operations comprising:
obtaining a training dataset including a population and achievement of a metric by the population;
identifying a predefined number of attributes of the population from the training dataset including the population; and
training a machine learning model using the training dataset to generate a trained machine learning model that values a segment of the population based on a significance of respective attributes of the predefined number of attributes on the achievement of the metric, the training using a penalty term that is automatically adjusted through successive training iterations using different portions of the training dataset and is configured to adjust bias and variance of the machine learning model as part of regularization to reduce over fitting and under fitting of the machine learning model, the model being an ensemble model formed using a plurality of sub-models having weighted contributions towards an overall result of the ensemble model that describes the achievement of the metric by the population, the significance quantified as a score by adjusting a weight of each of the respective attributes to determine a relative effect of the respective attributes on the metric, the score generated from the training dataset including the achievement of the metric by the population.