public class NaiveBayesModel extends ProbabilisticClassificationModel<Vector,NaiveBayesModel> implements MLWritable
NaiveBayes
param: pi log of class priors, whose dimension is C (number of classes)
param: theta log of class conditional probabilities, whose dimension is C (number of classes)
by D (number of features)Modifier and Type | Method and Description |
---|---|
protected static <T> T |
$(Param<T> param) |
static Params |
clear(Param<?> param) |
NaiveBayesModel |
copy(ParamMap extra)
Creates a copy of this instance with the same UID and some extra params.
|
protected static <T extends Params> |
copyValues(T to,
ParamMap extra) |
protected static <T extends Params> |
copyValues$default$2() |
protected static <T extends Params> |
defaultCopy(ParamMap extra) |
static java.lang.String |
explainParam(Param<?> param) |
static java.lang.String |
explainParams() |
static ParamMap |
extractParamMap() |
static ParamMap |
extractParamMap(ParamMap extra) |
static Param<java.lang.String> |
featuresCol() |
Param<java.lang.String> |
featuresCol()
Param for features column name.
|
protected static DataType |
featuresDataType() |
static <T> scala.Option<T> |
get(Param<T> param) |
static <T> scala.Option<T> |
getDefault(Param<T> param) |
static java.lang.String |
getFeaturesCol() |
java.lang.String |
getFeaturesCol() |
static java.lang.String |
getLabelCol() |
java.lang.String |
getLabelCol() |
static java.lang.String |
getModelType() |
java.lang.String |
getModelType() |
static <T> T |
getOrDefault(Param<T> param) |
static Param<java.lang.Object> |
getParam(java.lang.String paramName) |
static java.lang.String |
getPredictionCol() |
java.lang.String |
getPredictionCol() |
static java.lang.String |
getProbabilityCol() |
static java.lang.String |
getRawPredictionCol() |
java.lang.String |
getRawPredictionCol() |
static double |
getSmoothing() |
double |
getSmoothing() |
static double[] |
getThresholds() |
static <T> boolean |
hasDefault(Param<T> param) |
static boolean |
hasParam(java.lang.String paramName) |
static boolean |
hasParent() |
protected static void |
initializeLogIfNecessary(boolean isInterpreter) |
static boolean |
isDefined(Param<?> param) |
static boolean |
isSet(Param<?> param) |
protected static boolean |
isTraceEnabled() |
static Param<java.lang.String> |
labelCol() |
Param<java.lang.String> |
labelCol()
Param for label column name.
|
static NaiveBayesModel |
load(java.lang.String path) |
protected static org.slf4j.Logger |
log() |
protected static void |
logDebug(scala.Function0<java.lang.String> msg) |
protected static void |
logDebug(scala.Function0<java.lang.String> msg,
java.lang.Throwable throwable) |
protected static void |
logError(scala.Function0<java.lang.String> msg) |
protected static void |
logError(scala.Function0<java.lang.String> msg,
java.lang.Throwable throwable) |
protected static void |
logInfo(scala.Function0<java.lang.String> msg) |
protected static void |
logInfo(scala.Function0<java.lang.String> msg,
java.lang.Throwable throwable) |
protected static java.lang.String |
logName() |
protected static void |
logTrace(scala.Function0<java.lang.String> msg) |
protected static void |
logTrace(scala.Function0<java.lang.String> msg,
java.lang.Throwable throwable) |
protected static void |
logWarning(scala.Function0<java.lang.String> msg) |
protected static void |
logWarning(scala.Function0<java.lang.String> msg,
java.lang.Throwable throwable) |
static Param<java.lang.String> |
modelType() |
Param<java.lang.String> |
modelType()
The model type which is a string (case-sensitive).
|
int |
numClasses() |
int |
numFeatures() |
static Param<?>[] |
params() |
static void |
parent_$eq(Estimator<M> x$1) |
static Estimator<M> |
parent() |
Vector |
pi() |
protected static double |
predict(FeaturesType features) |
static Param<java.lang.String> |
predictionCol() |
Param<java.lang.String> |
predictionCol()
Param for prediction column name.
|
protected static Vector |
predictProbability(FeaturesType features) |
protected Vector |
predictRaw(Vector features) |
protected static double |
probability2prediction(Vector probability) |
static Param<java.lang.String> |
probabilityCol() |
protected static double |
raw2prediction(Vector rawPrediction) |
protected static Vector |
raw2probability(Vector rawPrediction) |
protected Vector |
raw2probabilityInPlace(Vector rawPrediction)
Estimate the probability of each class given the raw prediction,
doing the computation in-place.
|
static Param<java.lang.String> |
rawPredictionCol() |
Param<java.lang.String> |
rawPredictionCol()
Param for raw prediction (a.k.a.
|
static MLReader<NaiveBayesModel> |
read() |
static void |
save(java.lang.String path) |
static <T> Params |
set(Param<T> param,
T value) |
protected static Params |
set(ParamPair<?> paramPair) |
protected static Params |
set(java.lang.String param,
java.lang.Object value) |
protected static <T> Params |
setDefault(Param<T> param,
T value) |
protected static Params |
setDefault(scala.collection.Seq<ParamPair<?>> paramPairs) |
static M |
setFeaturesCol(java.lang.String value) |
static M |
setParent(Estimator<M> parent) |
static M |
setPredictionCol(java.lang.String value) |
static M |
setProbabilityCol(java.lang.String value) |
static M |
setRawPredictionCol(java.lang.String value) |
static M |
setThresholds(double[] value) |
static DoubleParam |
smoothing() |
DoubleParam |
smoothing()
The smoothing parameter.
|
Matrix |
theta() |
static DoubleArrayParam |
thresholds() |
java.lang.String |
toString() |
static Dataset<Row> |
transform(Dataset<?> dataset) |
static Dataset<Row> |
transform(Dataset<?> dataset,
ParamMap paramMap) |
static Dataset<Row> |
transform(Dataset<?> dataset,
ParamPair<?> firstParamPair,
ParamPair<?>... otherParamPairs) |
static Dataset<Row> |
transform(Dataset<?> dataset,
ParamPair<?> firstParamPair,
scala.collection.Seq<ParamPair<?>> otherParamPairs) |
protected static Dataset<Row> |
transformImpl(Dataset<?> dataset) |
static StructType |
transformSchema(StructType schema) |
protected static StructType |
transformSchema(StructType schema,
boolean logging) |
java.lang.String |
uid()
An immutable unique ID for the object and its derivatives.
|
protected static StructType |
validateAndTransformSchema(StructType schema,
boolean fitting,
DataType featuresDataType) |
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.
|
static void |
validateParams() |
MLWriter |
write()
Returns an
MLWriter instance for this ML instance. |
normalizeToProbabilitiesInPlace, predictProbability, probability2prediction, raw2prediction, raw2probability, setProbabilityCol, setThresholds, transform
predict, setRawPredictionCol
featuresDataType, setFeaturesCol, setPredictionCol, transformImpl, transformSchema
transform, transform, transform
transformSchema
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
save
clear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn, validateParams
public static MLReader<NaiveBayesModel> read()
public static NaiveBayesModel load(java.lang.String path)
public static Param<?>[] params()
public static void validateParams()
public static java.lang.String explainParam(Param<?> param)
public static java.lang.String explainParams()
public static final boolean isSet(Param<?> param)
public static final boolean isDefined(Param<?> param)
public static boolean hasParam(java.lang.String paramName)
public static Param<java.lang.Object> getParam(java.lang.String paramName)
protected static final Params set(java.lang.String param, java.lang.Object value)
public static final <T> scala.Option<T> get(Param<T> param)
public static final <T> T getOrDefault(Param<T> param)
protected static final <T> T $(Param<T> param)
public static final <T> scala.Option<T> getDefault(Param<T> param)
public static final <T> boolean hasDefault(Param<T> param)
public static final ParamMap extractParamMap()
protected static java.lang.String logName()
protected static org.slf4j.Logger log()
protected static void logInfo(scala.Function0<java.lang.String> msg)
protected static void logDebug(scala.Function0<java.lang.String> msg)
protected static void logTrace(scala.Function0<java.lang.String> msg)
protected static void logWarning(scala.Function0<java.lang.String> msg)
protected static void logError(scala.Function0<java.lang.String> msg)
protected static void logInfo(scala.Function0<java.lang.String> msg, java.lang.Throwable throwable)
protected static void logDebug(scala.Function0<java.lang.String> msg, java.lang.Throwable throwable)
protected static void logTrace(scala.Function0<java.lang.String> msg, java.lang.Throwable throwable)
protected static void logWarning(scala.Function0<java.lang.String> msg, java.lang.Throwable throwable)
protected static void logError(scala.Function0<java.lang.String> msg, java.lang.Throwable throwable)
protected static boolean isTraceEnabled()
protected static void initializeLogIfNecessary(boolean isInterpreter)
protected static StructType transformSchema(StructType schema, boolean logging)
public static Dataset<Row> transform(Dataset<?> dataset, ParamPair<?> firstParamPair, scala.collection.Seq<ParamPair<?>> otherParamPairs)
public static Dataset<Row> transform(Dataset<?> dataset, ParamPair<?> firstParamPair, ParamPair<?>... otherParamPairs)
public static Estimator<M> parent()
public static void parent_$eq(Estimator<M> x$1)
public static M setParent(Estimator<M> parent)
public static boolean hasParent()
public static final Param<java.lang.String> labelCol()
public static final java.lang.String getLabelCol()
public static final Param<java.lang.String> featuresCol()
public static final java.lang.String getFeaturesCol()
public static final Param<java.lang.String> predictionCol()
public static final java.lang.String getPredictionCol()
public static M setFeaturesCol(java.lang.String value)
public static M setPredictionCol(java.lang.String value)
protected static DataType featuresDataType()
public static StructType transformSchema(StructType schema)
public static final Param<java.lang.String> rawPredictionCol()
public static final java.lang.String getRawPredictionCol()
public static M setRawPredictionCol(java.lang.String value)
protected static double predict(FeaturesType features)
public static final Param<java.lang.String> probabilityCol()
public static final java.lang.String getProbabilityCol()
public static final DoubleArrayParam thresholds()
public static double[] getThresholds()
protected static StructType validateAndTransformSchema(StructType schema, boolean fitting, DataType featuresDataType)
public static M setProbabilityCol(java.lang.String value)
public static M setThresholds(double[] value)
protected static double raw2prediction(Vector rawPrediction)
protected static Vector predictProbability(FeaturesType features)
protected static double probability2prediction(Vector probability)
public static final DoubleParam smoothing()
public static final double getSmoothing()
public static final Param<java.lang.String> modelType()
public static final java.lang.String getModelType()
public static void save(java.lang.String path) throws java.io.IOException
java.io.IOException
public java.lang.String uid()
Identifiable
uid
in interface Identifiable
uid
in class ProbabilisticClassificationModel<Vector,NaiveBayesModel>
public Vector pi()
public Matrix theta()
public int numFeatures()
numFeatures
in class ProbabilisticClassificationModel<Vector,NaiveBayesModel>
public int numClasses()
numClasses
in class ProbabilisticClassificationModel<Vector,NaiveBayesModel>
protected Vector predictRaw(Vector features)
predictRaw
in class ProbabilisticClassificationModel<Vector,NaiveBayesModel>
protected Vector raw2probabilityInPlace(Vector rawPrediction)
ProbabilisticClassificationModel
This internal method is used to implement transform()
and output probabilityCol
.
raw2probabilityInPlace
in class ProbabilisticClassificationModel<Vector,NaiveBayesModel>
rawPrediction
- (undocumented)public NaiveBayesModel copy(ParamMap extra)
Params
copy
in interface Params
copy
in class ProbabilisticClassificationModel<Vector,NaiveBayesModel>
extra
- (undocumented)defaultCopy()
public java.lang.String toString()
toString
in interface Identifiable
toString
in class ProbabilisticClassificationModel<Vector,NaiveBayesModel>
public MLWriter write()
MLWritable
MLWriter
instance for this ML instance.write
in interface MLWritable
public DoubleParam smoothing()
public double getSmoothing()
public Param<java.lang.String> modelType()
public java.lang.String getModelType()
public StructType validateAndTransformSchema(StructType schema, boolean fitting, DataType featuresDataType)
public Param<java.lang.String> rawPredictionCol()
public java.lang.String getRawPredictionCol()
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.public Param<java.lang.String> labelCol()
public java.lang.String getLabelCol()
public Param<java.lang.String> featuresCol()
public java.lang.String getFeaturesCol()
public Param<java.lang.String> predictionCol()
public java.lang.String getPredictionCol()