Patent ID: 11954300
Assignee: PALANTIR TECHNOLOGIES INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 5:
6. A computer implemented system, comprising:
one or more processors; and
a machine-readable storage device comprising processor-executable instructions that,
when executed by the one or more processors, cause the one or more processors to perform operations comprising:
causing, by one or more processors of a machine, presentation of a graphical user interface having a set of selectable graphical interface elements including a first graphical interface element representing a set of data sets, a second graphical interface element representing a set of model families,
receiving, by the one or more processors of the machine, a selection of a particular data set through the graphical user interface, the particular data set including a set of values;
receiving, by the one or more processors of the machine, a selection of a first machine-learning algorithm and a second machine-learning algorithm through the graphical user interface, the first machine-learning algorithm configured to generate a first machine-learning model for
the set of values and the second machine-learning algorithm configured to generate a second machine-learning model for the set of values; and
in response to selection of the first machine-learning algorithm and the second machine-learning algorithm:
iteratively executing, by the one or more processors of the machine, the first machine-learning algorithm, using a first iteration order to process the set of values of the particular data set and generate a plurality of first machine-learning models, the first iteration order determined based on a first set of upper and lower bound values and a first step value indicating an order of iterations occurring between the first set of upper and lower bound values for the first machine-learning algorithm;
iteratively executing, by the one or more processors of the machine, the second machine-learning algorithm, using a second iteration order to process the set of values of the particular data set and generate a plurality of second machine-learning models, the second iteration order determined based on a second set of upper and lower bound values and a second step value indicating an order of iterations occurring between the second set of upper and lower bound values for the second machine-learning algorithm;
determining, by the one or more processors of the machine, one or more comparison metric values for data output by each of the plurality of first machine-learning models and the plurality of second machine-learning models; and
causing presentation, by the one or more processors of the machine, of the comparison metric values for the data output by the plurality of first machine-learning models and the plurality of second machine-learning models.