InforSense
Embedding Intelligence Throughout the Enterprise
 

ADVANCED ANALYTICS

Interactively build and optimize analytical applications

 

Key Benefits:

  • Wizard-driven model building Studios allow users to build and optimize models faster
  • InforSense workflows are automatically generated to form a clear record of how to analyse data
  • Connectors to other analytical engines enable analysts to incorporate their own scripts and programs within a larger analytical process

The InforSense Advanced Analytics package is a series of data mining analytics tools that extend InforSense. It is designed to support and enhance the work performed by data analysts using InforSense. The suite contains the following tools:

 

  • Analytical Algorithms to support Classification, Clustering, Association, Regression and Multi-variate analysis of data.
  • Classification and Clustering Studios are a guided environments to enable users to choose from "best practice" predictive and descriptive modelling workflows and to combine these with the analysts' own preferences for data preparation, feature selection, modelling and evaluations
  • Interactive Decision Tree enables users to combine their own understanding of the business problems with Decision Tree algorithms to determine the best choice of splits for a specific application.
  • Analytical Connectors - InforSense provides connectors to R, Matlab and SAS

Following are two example applications where InforSense Advanced Analytics has been applied.

Credit Risk Scoring

InforSense Classification Studio has been used to build a series of predictive models that can be used as the analytical engines within Probability of Default (PD) calculation. Using the Classification Studio, data was collected about previous loan applications and whether the loan had been defaulted. Using the Classification Studio environment, models about which customers were likely to default were built and compared. The Classification Studio was used both to aid users in the interpretation of the models, using its diagnostic tools, as well as to compare models built using different classification approaches in order to select the best model for the applications.

Microarray Data Analysis

For Microarray data analysis, the de-facto standard for normalization methods is provided by Bio-Conductor using the R Connector. From the InforSense Advanced Analytics package, users are able to combine the Bio-Conductor methods directly in an analytical workflow that enables users to normalize and then use other methods, including the InforSense Classification and Clustering Studios, to perform analytic operations.

 

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