public class IsotonicRegressionModel extends Model<IsotonicRegressionModel> implements MLWritable
For detailed rules see org.apache.spark.mllib.regression.IsotonicRegressionModel.predict()
.
param: oldModel A IsotonicRegressionModel
model trained by IsotonicRegression
.
Modifier and Type | Method and Description |
---|---|
protected static <T> T |
$(Param<T> param) |
Vector |
boundaries()
Boundaries in increasing order for which predictions are known.
|
static Params |
clear(Param<?> param) |
IsotonicRegressionModel |
copy(ParamMap extra)
Creates a copy of this instance with the same UID and some extra params.
|
protected static <T extends Params> |
copyValues(T to,
ParamMap extra) |
protected static <T extends Params> |
copyValues$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) |
protected static RDD<scala.Tuple3<java.lang.Object,java.lang.Object,java.lang.Object>> |
extractWeightedLabeledPoints(Dataset<?> dataset) |
RDD<scala.Tuple3<java.lang.Object,java.lang.Object,java.lang.Object>> |
extractWeightedLabeledPoints(Dataset<?> dataset)
Extracts (label, feature, weight) from input dataset.
|
static IntParam |
featureIndex() |
IntParam |
featureIndex()
Param for the index of the feature if
featuresCol is a vector column (default: 0 ), no
effect otherwise. |
static Param<java.lang.String> |
featuresCol() |
static <T> scala.Option<T> |
get(Param<T> param) |
static <T> scala.Option<T> |
getDefault(Param<T> param) |
static int |
getFeatureIndex() |
int |
getFeatureIndex() |
static java.lang.String |
getFeaturesCol() |
static boolean |
getIsotonic() |
boolean |
getIsotonic() |
static java.lang.String |
getLabelCol() |
static <T> T |
getOrDefault(Param<T> param) |
static Param<java.lang.Object> |
getParam(java.lang.String paramName) |
static java.lang.String |
getPredictionCol() |
static java.lang.String |
getWeightCol() |
static <T> boolean |
hasDefault(Param<T> param) |
static boolean |
hasParam(java.lang.String paramName) |
static boolean |
hasParent() |
protected static boolean |
hasWeightCol() |
boolean |
hasWeightCol()
Checks whether the input has weight column.
|
protected static void |
initializeLogIfNecessary(boolean isInterpreter) |
static boolean |
isDefined(Param<?> param) |
static BooleanParam |
isotonic() |
BooleanParam |
isotonic()
Param for whether the output sequence should be isotonic/increasing (true) or
antitonic/decreasing (false).
|
static boolean |
isSet(Param<?> param) |
protected static boolean |
isTraceEnabled() |
static Param<java.lang.String> |
labelCol() |
static IsotonicRegressionModel |
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<?>[] |
params() |
static void |
parent_$eq(Estimator<M> x$1) |
static Estimator<M> |
parent() |
static Param<java.lang.String> |
predictionCol() |
Vector |
predictions()
Predictions associated with the boundaries at the same index, monotone because of isotonic
regression.
|
static MLReader<IsotonicRegressionModel> |
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) |
IsotonicRegressionModel |
setFeatureIndex(int value) |
IsotonicRegressionModel |
setFeaturesCol(java.lang.String value) |
static M |
setParent(Estimator<M> parent) |
IsotonicRegressionModel |
setPredictionCol(java.lang.String value) |
static java.lang.String |
toString() |
Dataset<Row> |
transform(Dataset<?> dataset)
Transforms the input dataset.
|
StructType |
transformSchema(StructType schema)
:: DeveloperApi ::
|
java.lang.String |
uid()
An immutable unique ID for the object and its derivatives.
|
protected static StructType |
validateAndTransformSchema(StructType schema,
boolean fitting) |
StructType |
validateAndTransformSchema(StructType schema,
boolean fitting)
Validates and transforms input schema.
|
static void |
validateParams() |
static Param<java.lang.String> |
weightCol() |
MLWriter |
write()
Returns an
MLWriter instance for this ML instance. |
transform, transform, transform
transformSchema
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
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
toString
save
public static MLReader<IsotonicRegressionModel> read()
public static IsotonicRegressionModel load(java.lang.String path)
public static java.lang.String toString()
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 $(Param<T> param)
public static final <T> scala.Option<T> getDefault(Param<T> param)
public static final <T> boolean hasDefault(Param<T> param)
public static final ParamMap extractParamMap()
protected static java.lang.String logName()
protected static org.slf4j.Logger log()
protected static void logInfo(scala.Function0<java.lang.String> msg)
protected static void logDebug(scala.Function0<java.lang.String> msg)
protected static void logTrace(scala.Function0<java.lang.String> msg)
protected static void logWarning(scala.Function0<java.lang.String> msg)
protected static void logError(scala.Function0<java.lang.String> msg)
protected static void logInfo(scala.Function0<java.lang.String> msg, java.lang.Throwable throwable)
protected static void logDebug(scala.Function0<java.lang.String> msg, java.lang.Throwable throwable)
protected static void logTrace(scala.Function0<java.lang.String> msg, java.lang.Throwable throwable)
protected static void logWarning(scala.Function0<java.lang.String> msg, java.lang.Throwable throwable)
protected static void logError(scala.Function0<java.lang.String> msg, java.lang.Throwable throwable)
protected static boolean isTraceEnabled()
protected static void initializeLogIfNecessary(boolean isInterpreter)
public static Estimator<M> parent()
public static void parent_$eq(Estimator<M> x$1)
public static M setParent(Estimator<M> parent)
public static boolean hasParent()
public static final Param<java.lang.String> featuresCol()
public static final java.lang.String getFeaturesCol()
public static final Param<java.lang.String> labelCol()
public static final java.lang.String getLabelCol()
public static final Param<java.lang.String> predictionCol()
public static final java.lang.String getPredictionCol()
public static final Param<java.lang.String> weightCol()
public static final java.lang.String getWeightCol()
public static final BooleanParam isotonic()
public static final boolean getIsotonic()
public static final IntParam featureIndex()
public static final int getFeatureIndex()
protected static boolean hasWeightCol()
protected static RDD<scala.Tuple3<java.lang.Object,java.lang.Object,java.lang.Object>> extractWeightedLabeledPoints(Dataset<?> dataset)
protected static StructType validateAndTransformSchema(StructType schema, boolean fitting)
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
public IsotonicRegressionModel setFeaturesCol(java.lang.String value)
public IsotonicRegressionModel setPredictionCol(java.lang.String value)
public IsotonicRegressionModel setFeatureIndex(int value)
public Vector boundaries()
public Vector predictions()
public IsotonicRegressionModel copy(ParamMap extra)
Params
copy
in interface Params
copy
in class Model<IsotonicRegressionModel>
extra
- (undocumented)defaultCopy()
public Dataset<Row> transform(Dataset<?> dataset)
Transformer
transform
in class Transformer
dataset
- (undocumented)public StructType transformSchema(StructType schema)
PipelineStage
Derives the output schema from the input schema.
transformSchema
in class PipelineStage
schema
- (undocumented)public MLWriter write()
MLWritable
MLWriter
instance for this ML instance.write
in interface MLWritable
public BooleanParam isotonic()
public boolean getIsotonic()
public IntParam featureIndex()
featuresCol
is a vector column (default: 0
), no
effect otherwise.public int getFeatureIndex()
public boolean hasWeightCol()
public RDD<scala.Tuple3<java.lang.Object,java.lang.Object,java.lang.Object>> extractWeightedLabeledPoints(Dataset<?> dataset)
dataset
- (undocumented)public StructType validateAndTransformSchema(StructType schema, boolean fitting)
schema
- input schemafitting
- whether this is in fitting or prediction