Determining a Type of Predictive Model for Training Data

摘要

A computer-implemented method includes receiving, in a system of one or more computers, training data for predictive modeling, the training data including a plurality of categories; determining, by the system, one or more attributes of the training data; identifying, by the system in a mapping of attributes to types of predictive models, a type of predictive model that is mapped to at least one of the one or more attributes; obtaining a utility function for the predictive model of the identified type, the utility function specifying importance of the plurality of categories relative to each other; and generating, based on the training data and the utility function, a predictive model of the identified type.

主权项

1. A computer-implemented method comprising:
receiving, in a system of one or more computers, a set of training data for predictive modeling; determining, by the system, one or more attributes of the training data; identifying, by the system in a mapping of attributes to types of predictive models, a type of predictive model that is mapped to at least one of the one or more attributes; obtaining a utility function that specifies a first weighted value to be applied to a first item of training data in the set and that further specifies a second, different weighted value to be applied to a second, different item of training data in the set, with a weighted value for an item of training data specifying an importance of the item of training data, relative to another importance of another item of training data; assigning, based on the utility function, (i) the first weighted value to the first item of training data in the set, and (ii) the second, different weighted value to the second, different item of training data in the set; and training, based on assigning the first and second weighted values, a predictive model of the identified type.