Visualization and exploration of probabilistic models for multiple instances

A system for facilitating data exploration in a computing environment, comprising:

• one or more computers with executable instructions that when executed cause the system to:
• receive a multidimensional dataset;
• execute machine learning logic to perform a booting operation to initiate a graphical user interface (GUI) to be used in exploring the multidimensional dataset;
• in conjunction with performing the booting operation, determine, by the machine learning logic, whether training of one or more probabilistic models representing the multidimensional dataset is necessary to provide an interactive representation thereof;
• responsive to determining the training is necessary, train the one or more probabilistic models using the multidimensional dataset;
• responsive to determining the training is unnecessary, build one or more aggregation functions using multidimensional dataset;
• and
• provide visualization and exploration of the interactive representation of the one or more probabilistic models for each one of a set of instances using the multidimensional dataset, wherein each of a plurality of dimensions are ranked according to a degree of relevance associated with the set of instances, wherein the ranking indicates those of the plurality of dimensions that are included in the interactive representation for visualization and exploration.

A computer program product for facilitating data exploration in a computing environment, the computer program product comprising:

• one or more non-transitory computer readable storage media, and program instructions collectively stored on the one or more computer readable storage media, the program instruction comprising:
• program instructions to receive a multidimensional dataset;
• program instructions to execute machine learning logic to perform a booting operation to initiate a graphical user interface (GUI) to be used in exploring the multidimensional dataset;
• program instructions to, in conjunction with performing the booting operation, determine, by the machine learning logic, whether training of one or more probabilistic models representing the multidimensional dataset is necessary to provide an interactive representation thereof;
• program instructions to, responsive to determining the training is necessary, train the one or more probabilistic models using the multidimensional dataset;
• program instructions to, responsive to determining the training is unnecessary, build one or more aggregation functions using multidimensional dataset;
• and
• program instructions to provide visualization and exploration of the interactive representation of the one or more probabilistic models for each one of a set of instances using the multidimensional dataset, wherein each of a plurality of dimensions are ranked according to a degree of relevance associated with the set of instances, wherein the ranking indicates those of the plurality of dimensions that are included in the interactive representation for visualization and exploration.