Interactive interfaces for machine learning model evaluations
First Claim
Patent Images
1. A system, comprising:
- one or more computing devices configured to;
train a machine learning model to generate values of one or more output variables corresponding to respective observation records at a machine learning service of a provider network, wherein the one or more output variables include a particular output variable;
subsequent to the training;
generate an interactive graphical interface that displays a first set of data produced by one or more evaluation runs of the machine learning model performed using respective evaluation data sets, wherein the first set of data comprises at least (a) a statistical distribution of the particular output variable, and (b) a first prediction quality metric of the machine learning model;
receive input from a client via a first graphical control of the interactive graphical interface to modify a first prediction interpretation threshold, wherein the first prediction interpretation threshold specifies how the particular output variable is interpreted, wherein the modification is performed without modifying the machine learning model;
determine, based at least in part on the input from the client via the first graphical control, a target value of the first prediction interpretation threshold;
initiate a display, via the interactive graphical interface, of a change to the first prediction quality metric resulting from a selection of the target value;
in response to a request transmitted by the client via the interactive graphical interface, save the target value in a persistent repository of the machine learning service; and
utilize the saved target value to interpret the particular output variable and generate one or more prediction results of a subsequent run of the machine learning model.
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Abstract
A first data set corresponding to an evaluation run of a model is generated at a machine learning service for display via an interactive interface. The data set includes a prediction quality metric. A target value of an interpretation threshold associated with the model is determined based on a detection of a particular client'"'"'s interaction with the interface. An indication of a change to the prediction quality metric that results from the selection of the target value may be initiated.
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Citations
24 Claims
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1. A system, comprising:
one or more computing devices configured to; train a machine learning model to generate values of one or more output variables corresponding to respective observation records at a machine learning service of a provider network, wherein the one or more output variables include a particular output variable; subsequent to the training; generate an interactive graphical interface that displays a first set of data produced by one or more evaluation runs of the machine learning model performed using respective evaluation data sets, wherein the first set of data comprises at least (a) a statistical distribution of the particular output variable, and (b) a first prediction quality metric of the machine learning model; receive input from a client via a first graphical control of the interactive graphical interface to modify a first prediction interpretation threshold, wherein the first prediction interpretation threshold specifies how the particular output variable is interpreted, wherein the modification is performed without modifying the machine learning model; determine, based at least in part on the input from the client via the first graphical control, a target value of the first prediction interpretation threshold; initiate a display, via the interactive graphical interface, of a change to the first prediction quality metric resulting from a selection of the target value; in response to a request transmitted by the client via the interactive graphical interface, save the target value in a persistent repository of the machine learning service; and utilize the saved target value to interpret the particular output variable and generate one or more prediction results of a subsequent run of the machine learning model. - View Dependent Claims (2, 3, 4, 5)
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6. A method, comprising:
performing, by one or more computing devices; training a machine learning model to generate values of one or more output variables corresponding to respective observation records, wherein the one or more output variables include a particular output variable; subsequent to the training; generating an interactive graphical interface that displays a first set of data produced by one or more evaluation runs of the machine learning model, wherein the first set of data includes at least a first prediction quality metric of the machine learning model; receiving input from a client via a first graphical control of the interactive graphical interface to modify a first prediction interpretation threshold, wherein the first prediction interpretation threshold specifies how the particular output variable is interpreted, wherein the modification is performed without modifying the machine learning model; determining, based at least in part on the input from the client via the first graphical control, a target value of the first prediction interpretation threshold; initiating a display, via the interactive graphical interface, of a change to the first prediction quality metric resulting from a selection of the target value; and obtaining, using the target value, interpretations of the particular output variable to generate one or more prediction results of a subsequent run of the machine learning model. - View Dependent Claims (7, 8, 9, 10, 11, 12, 13, 14, 15, 16)
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17. A non-transitory computer-accessible storage medium storing program instructions that when executed on one or more processors:
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generate an interactive graphical interface that displays a first set of data produced by an evaluation run of a machine learning model subsequent to a training of the machine learning model, wherein the first set of data includes at least a first prediction quality metric of the machine learning mode; receive input from a client via a first graphical control of interactive graphical interface to modify a first interpretation threshold, wherein the first prediction interpretation threshold specifies how an output variable generated by the machine learning model is interpreted to generate prediction results, wherein the modification is performed without modifying the machine learning model; determine, based on the input from the client via the first graphical control, a target value of the first interpretation threshold; and initiate a display, via the interactive graphical interface, of a change to the first prediction quality metric resulting from a selection of the target value. - View Dependent Claims (18, 19, 20)
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21. A non-transitory computer-accessible storage medium storing program instructions that when executed on one or more processors:
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display a first set of data via an interactive interface during a particular interaction session with a client, wherein the first set of data corresponds to an evaluation run of a machine learning model subsequent to a training of the machine learning model, wherein the first set of data includes at least a first prediction quality metric associated with the evaluation run; transmit, to a server of a machine learning service during the particular interaction session, based on a detection of a particular interaction of the client with the interactive interface, a target value of a first interpretation threshold, wherein the first prediction interpretation threshold specifies how an output variable generated by the machine learning model is interpreted to generate prediction results, wherein the modification is performed without modifying the machine learning model; receive, from the server, an indication of a change to the first prediction quality metric resulting from a selection of the target value; and indicate, via the interactive interface, the change to the first prediction quality metric during the particular interaction session. - View Dependent Claims (22, 23, 24)
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Specification