Gains# Main Features
Modeling Algorithms
Efficient and effective stepwise variable selection
ATS (Adaptive Transformation Score) function
effectively displays relationship between independent variables and target variable
Adaptive logistic regression algorithm for binary dependent variables (see
comparison...
)
Adaptive Ordinary Least Square (OLS) algorithm for continuous dependent variables
Ability to check variable robustness even before building a model
Effective way to treat and safeguard against multicollinearity (highly correlated variables)
Modeling Process
Read directly in Excel (.csv) or SAS datasets, even without having SAS installed on local PC
Automatic treatment of missing values without excluding missing values from model development
"I can't think of modeling software that can generate, modify or validate a response model faster; and it offers the precision, flexibility and elegance that one might think comes only from customized nonlinear modeling programs and a lot of sophisticated thought."
"Gains# shows great strength at the model building stage. Among the tools we used in our recent projects, it is the
only one
that can produce stable models, and it takes the least amount of effort."
"No other modeling software I have used identifies variable transformations as effectively as Gains#."
"Gains# is very fast to learn."
Automatic integration of numerical and character-type variables
Flexible conversion of a variable from numerical-type to categorical-type or vice versa
One-click exporting of model codes or model scores to SAS and SQL
Model Evaluation
Easy to compare multiple models acrosss multiple datasets
Incorporates the most common statistical evaluation measures and charts, including
KS
,
the C statistics
,
Gini Coefficient
,
Gains Chart
and
Lift Curve
Various diagnostics tools for better understanding of models, such as relative model variable importance and multicollinearity detection tools
Customers Say ...
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