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java.lang.Objectorg.knime.base.node.mine.bfn.BasisFunctionPredictorCellFactory
public class BasisFunctionPredictorCellFactory
This predictor cell factory predicts the passed rows using the underlying basisfunction model.
Constructor Summary | |
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BasisFunctionPredictorCellFactory(DataColumnSpec[] specs,
boolean appendClassProps)
Create new predictor cell factory. |
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BasisFunctionPredictorCellFactory(DataTableSpec dataSpec,
DataColumnSpec[] specs,
int[] filteredColumns,
Map<DataCell,List<BasisFunctionPredictorRow>> model,
double dontKnowClass,
boolean normClass,
boolean appendClassProps)
Appends one column to the given data to make a prediction for each row using the model which contains one BasisFunctionPredictorRow
column. |
Method Summary | |
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DataCell[] |
getCells(DataRow row)
Predicts given row using the underlying basis function model. |
DataColumnSpec[] |
getColumnSpecs()
The column specs for the cells that are generated in the getCells() method. |
protected DataCell[] |
predict(DataRow row,
Map<DataCell,List<BasisFunctionPredictorRow>> model)
Predicts an unknown row to the given model. |
void |
setProgress(int curRowNr,
int rowCount,
RowKey lastKey,
ExecutionMonitor exec)
This method is called when a row has been processed. |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
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public BasisFunctionPredictorCellFactory(DataColumnSpec[] specs, boolean appendClassProps)
ColumnRearranger
with the appended model spec.
specs
- the appended column specsappendClassProps
- if class probabilities should be appendpublic BasisFunctionPredictorCellFactory(DataTableSpec dataSpec, DataColumnSpec[] specs, int[] filteredColumns, Map<DataCell,List<BasisFunctionPredictorRow>> model, double dontKnowClass, boolean normClass, boolean appendClassProps)
BasisFunctionPredictorRow
column.
dataSpec
- the spec of the test dataspecs
- names and types of the rule modelfilteredColumns
- use only those column for prediction (part of the
of training data)model
- the trained model as list of rowsdontKnowClass
- the don't know class probabilitynormClass
- normalize classification outputappendClassProps
- if class probabilities should be append
NullPointerException
- if one of the arguments is null
Method Detail |
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protected DataCell[] predict(DataRow row, Map<DataCell,List<BasisFunctionPredictorRow>> model)
row
- the row to predictmodel
- a list of rules
public DataCell[] getCells(DataRow row)
getCells
in interface CellFactory
row
- The row of interest.
public DataColumnSpec[] getColumnSpecs()
getColumnSpecs
in interface CellFactory
public void setProgress(int curRowNr, int rowCount, RowKey lastKey, ExecutionMonitor exec)
Note, you don't need to check exec.checkCanceled()
in
the implementation as this is done in the calling class.
setProgress
in interface CellFactory
curRowNr
- The number of the row just processedrowCount
- The total number of rows.lastKey
- The row's key.exec
- The execution monitor to report progress to.
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