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US 10,592,554 B1Granted
Systems, devices, and methods for parallelized data structure processing
AssigneeMassachusetts Mutual Life Insurance Company
InventorSears Merritt
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Abstract
This disclosure discloses systems, devices, and methods for parallelized data structure processing in context of machine learning and reverse proxy servers.
Claims20
A computer-implemented method comprising:
- performing, by a server, a hyperparameter selection based on a parallelized grid search algorithm configured to determine a number of decision trees, a depth of decision trees, and an amount of variables used during tree node splitting;
- randomly selecting, by the server, a first subset from a data set, wherein the data set contains a set of records with a plurality of fields, wherein each of the fields includes a value;
- constructing, by the server, a learned mortality model for each of the number of decision trees, the depth of decision trees, and the number of variables based on the values of the first subset;
- identifying, by the server, a second subset from the data set, wherein the second subset is exclusive of the first subset;
- evaluating, by the server, the learned mortality model based on the second subset via at least one of a concordance or a time-varying area under curve statistic such that a first mortality score is determined;
- presenting, by the server, a user interface for display on a client computer based on the first mortality score satisfying a predetermined threshold, wherein the user interface is configured to receive a user input from the client computer;
- receiving, by the server, the input from the client computer, wherein the input includes a user profile with an attribute;
- submitting, by the server, the input into the learned mortality model such that the model outputs a second mortality score based on the user profile with the attribute;
- and
- updating, by the server, the user interface for display on the client computer with the second mortality score.
7 more elements
A memory storing a set of instructions for execution by a processor, wherein the set of instructions instructs the processor to:
- perform a hyperparameter selection based on a parallelized grid search algorithm configured to determine a number of decision trees, a depth of decision trees, and an amount of variables used during tree node splitting;
- randomly select a first subset from a data set, wherein the data set contains a set of records with a plurality of fields, wherein each of the fields includes a value;
- construct a learned mortality model for each of the number of decision trees, the depth of decision trees, and the number of variables based on the values of the first subset;
- identify a second subset from the data set, wherein the second subset is exclusive of the first subset;
- evaluate the learned mortality model based on the second subset via at least one of a concordance or a time-varying area under curve statistic such that a first mortality score is determined;
- present a user interface for display on a client computer based on the first mortality score satisfying a predetermined threshold, wherein the user interface is configured to receive a user input from the client computer;
- receive the input from the client computer, wherein the input includes a user profile with an attribute;
- submit the input into the learned mortality model such that the model outputs a second mortality score based on the user profile with the attribute;
- and
- update the user interface for display on the client computer with the second mortality score.
7 more elements
Dependencies are inferred from the claim text.