APPARATUSES, METHODS, AND COMPUTER PROGRAM PRODUCTS FOR TRAINING AND USING MACHINE LEARNING MODELS IN SPARSE DATA ENVIRONMENTS USING TRANSFORMED DATA SETS
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United States of America
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Issued Date -
Nov 21, 2024
app pub date -
May 16, 2023
filing date -
May 16, 2023
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Abstract
Methods, apparatuses, and computer program products for generating predictions using machine learning model(s) are provided. For example, a computer-implemented method may include receiving raw historical data identifying historical value(s) corresponding to attribute value(s) of a set of ordered attribute values and transforming the raw historical data into parameter expanded data by, for each particular attribute value of the set of ordered attribute values, aggregating each of the historical value(s) that corresponds to the particular attribute value and each of the historical value(s) that corresponds to an attribute value that is greater than the particular attribute value. The machine learning model(s) are trained based on the parameter expanded data, which trained machine learning model(s) are used to generate the predictions.
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