Predictive model clustering

A computer program product for performing data clustering in a model property vector space, the computer program product comprising a computer-readable storage medium having a computer-readable program stored therein, wherein the computer-readable program, when executed on a processor, causes the processor to:

• receive input data from a database, the input data comprising a plurality of data instances in a data vector space, said plurality of data instances representing temporal features and geographical features information;
• define a model property vector specification for creating a model vector in a model property vector space, the model property vector specification including one or more categories of information to be predicted for a predictive analytic problem;
• use the input data and the model property vector specification to identify information from the input data, the identified information comprising a temporal feature attribute, a geographic feature attribute, and a categorical attribute information used to specify an item to be predicted for a predictive model;
• create a model property vector in the model property vector space from the identified information for each data instance of the plurality of data instances, said model property vector space being separate from the data vector space and having data instances defining a sub-space of the data vector space;
• identify a target number of clusters comprising a plurality of data clusters;
• use the target number of clusters and the data instances in the model property vector space to perform a data clustering procedure to cluster data in the model property vector space;
• generate an output from the data clustering procedure comprising a plurality of data segments and one or more clustering rules for the plurality of data clusters;
• and
• for each data cluster of the plurality of data clusters, construct a predictive model for each data segment of the plurality of data segments.

An apparatus for performing data clustering in a model property vector space, the apparatus comprising a processor and a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, provide:

• a model property vector creation module;
• a data clustering module operatively coupled to the model property vector creation module;
• and
• a predictive models training module operatively coupled to the data clustering module;
• wherein the model property vector creation module is configured to receive input data from a database, the input data comprising a plurality of data instances in a data vector space, said plurality of data instances representing temporal features and geographical features information;
• define a model property vector specification for creating a model vector in a model property vector space, the model property vector specification including one or more categories of information to be predicted for a predictive-analytic problem;
• use the input data and the model property vector specification to identify information from the input data, the identified information comprising a temporal feature attribute, a geographic feature attribute, and a categorical attribute information used to specify an item to be predicted for a predictive model;
• create a model property vector in the model property vector space from the identified information for each data instance of the plurality of data instances, said model property vector space being separate from the data vector space and having data instances defining a sub-space of the data vector space;
• and identify a target number of clusters comprising a plurality of data clusters;
• wherein the data clustering module is configured to use the target number of clusters and the data instances in the model property vector space to perform a data clustering procedure to cluster data in the model property vector space;
• and to generate an output from the data clustering procedure comprising a plurality of data segments and one or more clustering rules for the plurality of data clusters;
• and
• wherein the predictive models training module is configured, for each data cluster of the plurality of data clusters, to construct a predictive model for each data segment of the plurality of data segments.