TRAINING AN ENSEMBLE OF MACHINE LEARNING MODELS FOR CLASSIFICATION PREDICTION USING PROBABILITIES AND ENSEMBLE CONFIDENCE

A method including training predictor machine learning models (MLMs) using a first data set. The trained predictor MLMs are trained to predict classifications of data items in the first data set. The method also includes training confidence MLMs using second classifications, output by the trained pr...

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Hauptverfasser: Ran, Alexander, Lesner, Christopher
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creator Ran, Alexander
Lesner, Christopher
description A method including training predictor machine learning models (MLMs) using a first data set. The trained predictor MLMs are trained to predict classifications of data items in the first data set. The method also includes training confidence MLMs using second classifications, output by the trained predictor MLMs. The method also includes generating an aggregated ranked list of classes based on third classifications output by the trained predictor MLMs and second confidences output by the trained confidence MLMs. The method also includes training an ensemble confidence MLM using the aggregated ranked list of classes to generate a trained ensemble confidence MLM. The trained ensemble confidence MLM is trained to predict a corresponding selected classification for each corresponding data item in a training data set containing second data items similar to the first data items.
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subjects CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
title TRAINING AN ENSEMBLE OF MACHINE LEARNING MODELS FOR CLASSIFICATION PREDICTION USING PROBABILITIES AND ENSEMBLE CONFIDENCE
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