1. Variable Selection - Accelerator
An engine to select important predictors before any predictive modelling to get more accurate result in less time.
Several simple and complex variable/feature selection algorithms included.
This tool can eliminate redundant/ insignificant predictors.
Engine and UI developed on R Studio using the Shiny interface.
FEATURES
Identifies whether it is regression or classification problem based on the response variable.
Provides data snapshot, correlation matrix, manual feature inclusion/exclusion in the front end.
Applies different types of algorithms like step-wise Regression, CForest, Boruta, Random Forest etc.
Identifies best set of feature to predict response variable and provide ranks of the important variables.
APPLICATION AREAS
Human Resource
Analyze employee data to identify factors responsible for employee attrition and employee performance
Entertainment
Analyze TV rating data to identify variables which can be used to increase TV impressions.
Feedback of any Services
Find out factors which have most impact on customer feedbacks for any services like Restaurants, Transports etc. to serve your customers better.