Advanced analytical infrastructure for machine learning

Abstract

Machine learning systems and computerized methods to compare candidate machine learning algorithms are disclosed. The machine learning system comprises a machine learning algorithm library, a data input module to receive a dataset and a selection of machine learning models derived from the machine learning algorithm library, an experiment module, and an aggregation module. The experiment module is configured to train and evaluate each machine learning model to produce a performance result for each machine learning model. The aggregation module is configured to aggregate the performance results for all of the machine learning models to form performance comparison statistics. Computerized methods include receiving a dataset, receiving a selection of machine learning models, training and evaluating each machine learning model to produce a performance result for each machine learning model, aggregating the performance results to form performance comparison statistics, and presenting the performance comparison statistics.

Description

Technical field [0001] The present disclosure relates to advanced analytics infrastructure for machine learning. Background technique [0002] Machine learning is a process for analyzing data that uses a data set to determine a model (also called an independent variable or response variable) that maps input data (also called explanatory variables or predicted values) to output data (independent variables or response variables). Rules or functions). One type of machine learning is supervised learning, in which a model is trained using a data set that includes known output data for a sufficient amount of input data. Once the model is trained, it can be deployed, that is, applied to new input data to predict the desired output. [0003] Machine learning can be applied to regression problems (where the output data is digital, such as voltage, pressure, multiple cycles) and classification problems (where the output data is a label, category, and / or category, such as pass-fail, fail T...

AI Technical Summary

Problems solved by technology

[0006] A machine learning system that can be configured to test candidate machine learning algorithms for a particular data analysis problem

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