The
SNP Interaction Discovery
process performs a
penalized logistic regression
at different
lambda
levels (ranging from 2 through 4) and presents the
cross validation
statistics for these
models
and determine which level is best for prediction from that particular data set.
Cross validation consists of dividing the rows of a wide data set into two groups, labeling one as the test group and the other as the training group, and then, after setting aside the test group, fitting one or more
predictive models
only to the training set. The fitted models derived using the training set are then evaluated with the
predictor
variables of the test set to obtain predicted values. These values are then compared to the observed values. This process is repeated a specified number of times, using a different training/test division. Results are summarized and displayed side-by-side. Refer to
Cross Validation Model Comparison
for more information about this process.
Running this process using the
GeneticMarkerExample
sample setting generates the tabbed
Results
window shown below. Refer to the
SNP Interaction Discovery
process description for more information. Output from the process is organized into tabs. Each tab contains one or more plots, data panels, data filters, and other elements that facilitate your analysis.
The
Results
window contains the following panes:
This pane provides you with a space to view individual tabs within the
Results
window. Use the tabs to access and view the output plots and associated data sets.
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RMSE
: Displays results for the
Root Mean Square Error
performance criterion.
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AUC
: Present only when data contains binary
dependent variables
. Displays results for the area under the receiver operating characteristic (
ROC
) curve performance criterion.
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Accuracy
: Present only when data contains binary dependent variables. Displays results for the accuracy performance criterion.
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Reliability Diagrams
: Displays
reliability diagrams
for each method.
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Model Effects
: Hierarchically clusters effects chosen from each method.
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Click
to reveal the underlying data table associated with the current tab.
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Click
to reopen the completed process dialog used to generate this output.
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Click
to generate a
pdf
- or
rtf
-formatted report containing the plots and charts of selected tabs.
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Click
to close all graphics windows and underlying data sets associated with the output.
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