Full-featured implementation of Multivariate Adaptive Regression Splines (MARSplines) for regression problems; with automatic deployment.

**General**

**Detail of
computed results reported**. Detail of computed results; if Minimal
detail is requested, spreadsheets of model summary, model coefficients,
regression and descriptive statistics will be displayed; at the Comprehensive
level of detail, a spreadsheet of predictions and residuals as well as
their histogram plots will be displayed; in addition to the above, the
All results level will display a spreadsheet (if the 'Creates residual
statistics' option is selected) containing all data set variables and
their statistics including predictions and residuals.

**Missing
data deletion**. Specifies the substitution method for missing
data. Casewise excludes cases that contain any missing data for any of
the selected variables in the analysis. Mean substitution replaces missing
data by the means for the respective variables (Note: This option is not
applicable for categorical dependent and predictor variables)

**Generate
datasource, if N for input less than**. Generate a data source
for further analyses with other Data Miner nodes if the input data source
has fewer than k observations, as specified in this edit field; note that
parameter k (number of observations) will be evaluated against the number
of observations in the input data source, not the number of valid or selected
observations.

**Options**

**Maximum
number of basis functions**. Specifies the maximum number of
basis functions the model can have. The larger this number the more flexible
(complex) the resulting model will be.

**Degree of
interactions**. Specifies the degree of interactions between
the variables.

**Penalty
for adding basis functions**. Specifies the penalty (cost) for
selecting each basis function. The larger this smoothing parameter is
the fewer basis functions are selected.

**Threshold**.
Specifies a stopping threshold to prevent overfitting.

**Apply pruning**.
Apply pruning to control model complexity.

**Apply memory
limit**. Use this option to limit the maximum data size that
can be processed; note that very large data problems may require significant
memory and processing resources; modify the defaults only as needed.

**Memory limit**.
Use this option to set the maximum data size that can be processed.

**Creates
residual statistics**. Creates predicted and residual statistics
for each case depending on the selected level of details.

**Draw scatter
plots**. Draws the scatter plots of the independent variables
selected by MARSplines versus the dependent variables (observed and predicted
values).

**Results**

**Include
inputs**. Includes the independent variables in spreadsheets
and histograms.

**Include
outputs**. Includes the dependent variables in spreadsheets and
histograms.

**Include
predictions**. Includes predictions in spreadsheets and histograms.

**Include
residuals**. Includes residuals in spreadsheets and histograms.

**Deployment. **Deployment is
available if the Statistica installation is licensed for this feature.

**Generates
C/C++ code**. Generates C/C++ code for deployment of predictive
model.

**Generates SVB code**. Generates Statistica Visual
Basic code for deployment of predictive model.

**Generates
PMML code**. Generates PMML (Predictive Models Markup Language)
code for deployment of predictive model.. This code can be used via the
Rapid Deployment options to efficiently compute predictions for (score)
large data sets.