International Business Machines Corporation

Margaret J Vais

Jing-Yun Shyr

Damir Spisic

Marc S Altshuller

Neil Whitney

Daniel Jay Rope

Michael D Woods

A method for comparing predictive data models based on a predictive model search is provided. The method may include receiving a first and second portion of a set of data. The method may also include identifying a first and second variation of the second portion, wherein the first variation is different from the second variation. The method may further include generating first predictive data models based on the first variation, and second predictive data models based on the second variation. Additionally, the method may include applying a criteria to rank the first and second predictive data models based on predictive strength. The method may also include presenting a display of the ranked criteria, comprising the first portion, and a portion of the first and second predictive data models, wherein the portion of the first and second predictive data models are collectively ranked and presented according to the predictive strength.

Predictive model search by communicating comparative strength

Provided are techniques for summarizing statistical results. Multiple sets of statistical results are received, wherein each of the sets of statistical results are ordered according to interestingness. Insights are generated based on the multiple sets of statistical results. Relationships between the generated insights are identified. An executive summary is generated with a set of findings based on the identified relationships. An interactive visualization is provided with the generated insights based on the executive summary.

Interpretation of statistical results

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Chicago, IL, United States of America

Margaret J Vais