INTERACTIVE MACHINE LEARNING MODEL DEVELOPMENT
First Claim
1. An apparatus for interactive machine learning model development, the apparatus comprising:
- a memory storing a plurality of observations of data of a system, each of the plurality of observations of the data including values of a plurality of independent variables, and a value of a dependent variable; and
processing circuitry configured to access the memory, and execute an application to generate a visual environment including a graphical user interface (GUI) for interactive development of a machine learning model, according to an iterative process at least an iteration of which includes the apparatus being caused to at least;
access the memory including the plurality of observations of the data;
perform an interactive exploratory data analysis of the values of a set of independent variables from the plurality of independent variables for a set of observations from the plurality of observations of the data, in which infographics are automatically produced in the GUI to visually summarize the values of the set of independent variables, one or more of the set of independent variables or one or more of the set of observations being selected based on user input via the GUI;
perform an interactive feature construction and selection based on the interactive exploratory data analysis, and in which select independent variables from the plurality of independent variables are selected as or transformed into a set of features for use in building the machine learning model to predict the dependent variable, one or more of the select independent variables being selected as or transformed into the set of features based on user input via the GUI and the infographics automatically produced in the GUI; and
build the machine learning model using a machine learning algorithm, the set of features, and a training set produced from the set of features and the plurality of observations of the data, including values of the select independent variables, and the value of the dependent variable,wherein the interactive development of the machine learning model further includes the apparatus being caused to output the machine learning model for deployment to predict and thereby produce predictions of the dependent variable for additional observations of the data that exclude the value of the dependent variable, the predictions produced by the machine learning model being more accurate than produced by a corresponding machine learning model built without the interactive exploratory data analysis and the interactive feature construction and selection that include user input via the GUI.
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Abstract
A method is provided that includes generating a visual environment for interactive development of a machine learning (ML) model. The method includes accessing observations of data each of which includes values of independent variables and a dependent variable, and performing an interactive exploratory data analysis (EDA) of the values of a set of the independent variables. The method includes performing an interactive feature construction and selection based on the interactive EDA, and in which select independent variables are selected as or transformed into a set of features for use in building a ML model to predict the dependent variable. The method includes building the ML model using a ML algorithm, the set of features, and a training set produced from the set of features and observations of the data. And the method includes outputting the ML model for deployment to predict the dependent variable for additional observations of the data.
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Citations
24 Claims
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1. An apparatus for interactive machine learning model development, the apparatus comprising:
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a memory storing a plurality of observations of data of a system, each of the plurality of observations of the data including values of a plurality of independent variables, and a value of a dependent variable; and processing circuitry configured to access the memory, and execute an application to generate a visual environment including a graphical user interface (GUI) for interactive development of a machine learning model, according to an iterative process at least an iteration of which includes the apparatus being caused to at least; access the memory including the plurality of observations of the data; perform an interactive exploratory data analysis of the values of a set of independent variables from the plurality of independent variables for a set of observations from the plurality of observations of the data, in which infographics are automatically produced in the GUI to visually summarize the values of the set of independent variables, one or more of the set of independent variables or one or more of the set of observations being selected based on user input via the GUI; perform an interactive feature construction and selection based on the interactive exploratory data analysis, and in which select independent variables from the plurality of independent variables are selected as or transformed into a set of features for use in building the machine learning model to predict the dependent variable, one or more of the select independent variables being selected as or transformed into the set of features based on user input via the GUI and the infographics automatically produced in the GUI; and build the machine learning model using a machine learning algorithm, the set of features, and a training set produced from the set of features and the plurality of observations of the data, including values of the select independent variables, and the value of the dependent variable, wherein the interactive development of the machine learning model further includes the apparatus being caused to output the machine learning model for deployment to predict and thereby produce predictions of the dependent variable for additional observations of the data that exclude the value of the dependent variable, the predictions produced by the machine learning model being more accurate than produced by a corresponding machine learning model built without the interactive exploratory data analysis and the interactive feature construction and selection that include user input via the GUI. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A method of interactive machine learning model development, the method comprising:
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executing an application, via processing circuitry, to generate a visual environment including a graphical user interface (GUI) for interactive development of a machine learning model, according to an iterative process at least an iteration of which includes at least; accessing a plurality of observations of data of a system, each of the plurality of observations of the data including values of a plurality of independent variables, and a value of a dependent variable; performing an interactive exploratory data analysis of the values of a set of independent variables from the plurality of independent variables for a set of observations from the plurality of observations of the data, in which infographics are automatically produced in the GUI to visually summarize the values of the set of independent variables, one or more of the set of independent variables or one or more of the set of observations being selected based on user input via the GUI; performing an interactive feature construction and selection based on the interactive exploratory data analysis, and in which select independent variables from the plurality of independent variables are selected as or transformed into a set of features for use in building the machine learning model to predict the dependent variable, one or more of the select independent variables being selected as or transformed into the set of features based on user input via the GUI and the infographics automatically produced in the GUI; and building the machine learning model using a machine learning algorithm, the set of features, and a training set produced from the set of features and the plurality of observations of the data, including values of the select independent variables, and the value of the dependent variable; and outputting the machine learning model for deployment to predict and thereby produce predictions of the dependent variable for additional observations of the data that exclude the value of the dependent variable, the predictions produced by the machine learning model being more accurate than produced by a corresponding machine learning model built without the interactive exploratory data analysis and the interactive feature construction and selection that include user input via the GUI. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16)
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17. A non-transitory computer-readable storage medium for interactive machine learning model development, the computer-readable storage medium having computer-readable program code stored therein that in response to execution by processing circuitry, causes an apparatus to at least:
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generate a visual environment including a graphical user interface (GUI) for interactive development of a machine learning model, according to an iterative process at least an iteration of which includes the apparatus being caused to at least; access a plurality of observations of data of a system, each of the plurality of observations of the data including values of a plurality of independent variables, and a value of a dependent variable; perform an exploratory data analysis in which infographics are automatically produced in the GUI to visually summarize the values of a set of independent variables; perform a feature construction and selection based on the exploratory data analysis, and in which select independent variables are selected as or transformed into a set of features; and build the machine learning model using a machine learning algorithm, the set of features, and a training set produced from the set of features and the plurality of observations of the data, including values of the select independent variables, and the value of the dependent variable, wherein one or more of the exploratory data analysis, feature construction and selection, or build of the machine learning model is interactive and based on user input via the GUI, and wherein the interactive development of the machine learning model further includes the apparatus being caused to output the machine learning model for deployment to predict the dependent variable for additional observations of the data that exclude the value of the dependent variable, predictions produced by the machine learning model being more accurate than produced by a corresponding machine learning model built without the user input via the GUI. - View Dependent Claims (18, 19, 20, 21, 22, 23, 24)
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Specification