public class LogisticRegression extends Classifier<FeaturesType,E,M> implements Logging
Constructor and Description |
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LogisticRegression() |
LogisticRegression(String uid) |
Modifier and Type | Method and Description |
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LogisticRegression |
setElasticNetParam(double value)
Set the ElasticNet mixing parameter.
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LogisticRegression |
setFitIntercept(boolean value)
Whether to fit an intercept term.
|
LogisticRegression |
setMaxIter(int value)
Set the maximum number of iterations.
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E |
setProbabilityCol(String value) |
LogisticRegression |
setRegParam(double value)
Set the regularization parameter.
|
LogisticRegression |
setThreshold(double value) |
LogisticRegression |
setTol(double value)
Set the convergence tolerance of iterations.
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String |
uid() |
StructType |
validateAndTransformSchema(StructType schema,
boolean fitting,
DataType featuresDataType) |
StructType |
validateAndTransformSchema(StructType schema,
boolean fitting,
DataType featuresDataType)
Validates and transforms the input schema with the provided param map.
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setRawPredictionCol
copy, fit, setFeaturesCol, setLabelCol, setPredictionCol, transformSchema
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
initializeIfNecessary, initializeLogging, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning
clear, copyValues, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, setDefault, shouldOwn, validateParams
public LogisticRegression(String uid)
public LogisticRegression()
public String uid()
public LogisticRegression setRegParam(double value)
value
- (undocumented)public LogisticRegression setElasticNetParam(double value)
value
- (undocumented)public LogisticRegression setMaxIter(int value)
value
- (undocumented)public LogisticRegression setTol(double value)
value
- (undocumented)public LogisticRegression setFitIntercept(boolean value)
value
- (undocumented)public LogisticRegression setThreshold(double value)
public StructType validateAndTransformSchema(StructType schema, boolean fitting, DataType featuresDataType)
public E setProbabilityCol(String value)
public StructType validateAndTransformSchema(StructType schema, boolean fitting, DataType featuresDataType)
schema
- input schemafitting
- whether this is in fittingfeaturesDataType
- SQL DataType for FeaturesType.
E.g., VectorUDT
for vector features.