IsotonicRegressionModel (Spark 2.1.0 JavaDoc)

Object
- org.apache.spark.ml.PipelineStage
- - org.apache.spark.ml.Transformer
  - - org.apache.spark.ml.Model<IsotonicRegressionModel>
    - - org.apache.spark.ml.regression.IsotonicRegressionModel

All Implemented Interfaces:

java.io.Serializable, Params, Identifiable, MLWritable
```
public class IsotonicRegressionModel
extends Model<IsotonicRegressionModel>
implements MLWritable
```
Model fitted by IsotonicRegression. Predicts using a piecewise linear function.
For detailed rules see org.apache.spark.mllib.regression.IsotonicRegressionModel.predict().
param: oldModel A IsotonicRegressionModel model trained by IsotonicRegression.

See Also:
Serialized Form

Method Summary

Methods
Modifier and Type	Method and Description
`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.
`static String`	`explainParam(Param<?> param)`
`static String`	`explainParams()`
`static ParamMap`	`extractParamMap()`
`static ParamMap`	`extractParamMap(ParamMap extra)`
`RDD<scala.Tuple3<Object,Object,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<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 String`	`getFeaturesCol()`
`static boolean`	`getIsotonic()`
`boolean`	`getIsotonic()`
`static String`	`getLabelCol()`
`static <T> T`	`getOrDefault(Param<T> param)`
`static Param<Object>`	`getParam(String paramName)`
`static String`	`getPredictionCol()`
`static String`	`getWeightCol()`
`static <T> boolean`	`hasDefault(Param<T> param)`
`static boolean`	`hasParam(String paramName)`
`static boolean`	`hasParent()`
`boolean`	`hasWeightCol()` Checks whether the input has weight column.
`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)`
`static Param<String>`	`labelCol()`
`static IsotonicRegressionModel`	`load(String path)`
`static Param<?>[]`	`params()`
`static void`	`parent_$eq(Estimator<M> x$1)`
`static Estimator<M>`	`parent()`
`static Param<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(String path)`
`static <T> Params`	`set(Param<T> param, T value)`
`IsotonicRegressionModel`	`setFeatureIndex(int value)`
`IsotonicRegressionModel`	`setFeaturesCol(String value)`
`static M`	`setParent(Estimator<M> parent)`
`IsotonicRegressionModel`	`setPredictionCol(String value)`
`static String`	`toString()`
`Dataset<Row>`	`transform(Dataset<?> dataset)` Transforms the input dataset.
`StructType`	`transformSchema(StructType schema)` :: DeveloperApi ::
`String`	`uid()` An immutable unique ID for the object and its derivatives.
`StructType`	`validateAndTransformSchema(StructType schema, boolean fitting)` Validates and transforms input schema.
`static Param<String>`	`weightCol()`
`MLWriter`	`write()` Returns an `MLWriter` instance for this ML instance.

Methods inherited from class org.apache.spark.ml.Model
hasParent, parent, setParent

Methods inherited from class org.apache.spark.ml.Transformer
transform, transform, transform

Methods inherited from class Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.apache.spark.ml.param.Params
clear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn

Methods inherited from interface org.apache.spark.ml.util.Identifiable
toString

Methods inherited from interface org.apache.spark.ml.util.MLWritable
save

- Method Detail
  - read
```
public static MLReader<IsotonicRegressionModel> read()
```
  - load
```
public static IsotonicRegressionModel load(String path)
```
  - toString
```
public static String toString()
```
  - params
```
public static Param<?>[] params()
```
  - explainParam
```
public static String explainParam(Param<?> param)
```
  - explainParams
```
public static String explainParams()
```
  - isSet
```
public static final boolean isSet(Param<?> param)
```
  - isDefined
```
public static final boolean isDefined(Param<?> param)
```
  - hasParam
```
public static boolean hasParam(String paramName)
```
  - getParam
```
public static Param<Object> getParam(String paramName)
```
  - set
```
public static final <T> Params set(Param<T> param,
             T value)
```
  - get
```
public static final <T> scala.Option<T> get(Param<T> param)
```
  - clear
```
public static final Params clear(Param<?> param)
```
  - getOrDefault
```
public static final <T> T getOrDefault(Param<T> param)
```
  - getDefault
```
public static final <T> scala.Option<T> getDefault(Param<T> param)
```
  - hasDefault
```
public static final <T> boolean hasDefault(Param<T> param)
```
  - extractParamMap
```
public static final ParamMap extractParamMap(ParamMap extra)
```
  - extractParamMap
```
public static final ParamMap extractParamMap()
```
  - parent
```
public static Estimator<M> parent()
```
  - parent_$eq
```
public static void parent_$eq(Estimator<M> x$1)
```
  - setParent
```
public static M setParent(Estimator<M> parent)
```
  - hasParent
```
public static boolean hasParent()
```
  - featuresCol
```
public static final Param<String> featuresCol()
```
  - getFeaturesCol
```
public static final String getFeaturesCol()
```
  - labelCol
```
public static final Param<String> labelCol()
```
  - getLabelCol
```
public static final String getLabelCol()
```
  - predictionCol
```
public static final Param<String> predictionCol()
```
  - getPredictionCol
```
public static final String getPredictionCol()
```
  - weightCol
```
public static final Param<String> weightCol()
```
  - getWeightCol
```
public static final String getWeightCol()
```
  - isotonic
```
public static final BooleanParam isotonic()
```
  - getIsotonic
```
public static final boolean getIsotonic()
```
  - featureIndex
```
public static final IntParam featureIndex()
```
  - getFeatureIndex
```
public static final int getFeatureIndex()
```
  - save
```
public static void save(String path)
                 throws java.io.IOException
```
    Throws:
    
    java.io.IOException
  - uid
```
public String uid()
```
    Description copied from interface: Identifiable
    
    An immutable unique ID for the object and its derivatives.
    
    Specified by:
    
    uid in interface Identifiable
    
    Returns:
    (undocumented)
  - setFeaturesCol
```
public IsotonicRegressionModel setFeaturesCol(String value)
```
  - setPredictionCol
```
public IsotonicRegressionModel setPredictionCol(String value)
```
  - setFeatureIndex
```
public IsotonicRegressionModel setFeatureIndex(int value)
```
  - boundaries
```
public Vector boundaries()
```
    Boundaries in increasing order for which predictions are known.
  - predictions
```
public Vector predictions()
```
    Predictions associated with the boundaries at the same index, monotone because of isotonic regression.
    
    Returns:
    (undocumented)
  - copy
```
public IsotonicRegressionModel copy(ParamMap extra)
```
    Description copied from interface: Params
    
    Creates a copy of this instance with the same UID and some extra params. Subclasses should implement this method and set the return type properly. See defaultCopy().
    
    Specified by:
    
    copy in interface Params
    
    Specified by:
    
    copy in class Model<IsotonicRegressionModel>
    
    Parameters:
    extra - (undocumented)
    
    Returns:
    (undocumented)
  - transform
```
public Dataset<Row> transform(Dataset<?> dataset)
```
    Description copied from class: Transformer
    
    Transforms the input dataset.
    
    Specified by:
    
    transform in class Transformer
    
    Parameters:
    dataset - (undocumented)
    
    Returns:
    (undocumented)
  - transformSchema
```
public StructType transformSchema(StructType schema)
```
    Description copied from class: PipelineStage
    
    :: DeveloperApi ::
    Check transform validity and derive the output schema from the input schema.
    We check validity for interactions between parameters during transformSchema and raise an exception if any parameter value is invalid. Parameter value checks which do not depend on other parameters are handled by Param.validate().
    Typical implementation should first conduct verification on schema change and parameter validity, including complex parameter interaction checks.
    
    Specified by:
    
    transformSchema in class PipelineStage
    
    Parameters:
    schema - (undocumented)
    
    Returns:
    (undocumented)
  - write
```
public MLWriter write()
```
    Description copied from interface: MLWritable
    
    Returns an MLWriter instance for this ML instance.
    
    Specified by:
    
    write in interface MLWritable
    
    Returns:
    (undocumented)
  - isotonic
```
public BooleanParam isotonic()
```
    Param for whether the output sequence should be isotonic/increasing (true) or antitonic/decreasing (false). Default: true
    
    Returns:
    (undocumented)
  - getIsotonic
```
public boolean getIsotonic()
```
  - featureIndex
```
public IntParam featureIndex()
```
    Param for the index of the feature if featuresCol is a vector column (default: 0), no effect otherwise.
    
    Returns:
    (undocumented)
  - getFeatureIndex
```
public int getFeatureIndex()
```
  - hasWeightCol
```
public boolean hasWeightCol()
```
    Checks whether the input has weight column.
  - extractWeightedLabeledPoints
```
public RDD<scala.Tuple3<Object,Object,Object>> extractWeightedLabeledPoints(Dataset<?> dataset)
```
    Extracts (label, feature, weight) from input dataset.
    
    Parameters:
    dataset - (undocumented)
    
    Returns:
    (undocumented)
  - validateAndTransformSchema
```
public StructType validateAndTransformSchema(StructType schema,
                                    boolean fitting)
```
    Validates and transforms input schema.
    
    Parameters:
    schema - input schema
    fitting - whether this is in fitting or prediction
    
    Returns:
    output schema

Class IsotonicRegressionModel

Method Summary

Methods inherited from class org.apache.spark.ml.Model

Methods inherited from class org.apache.spark.ml.Transformer

Methods inherited from class Object

Methods inherited from interface org.apache.spark.ml.param.Params

Methods inherited from interface org.apache.spark.ml.util.Identifiable

Methods inherited from interface org.apache.spark.ml.util.MLWritable

Method Detail

read

load

toString

params

explainParam

explainParams

isSet

isDefined

hasParam

getParam

set

get

clear

getOrDefault

getDefault

hasDefault

extractParamMap

extractParamMap

parent

parent_$eq

setParent

hasParent

featuresCol

getFeaturesCol

labelCol

getLabelCol

predictionCol

getPredictionCol

weightCol

getWeightCol

isotonic

getIsotonic

featureIndex

getFeatureIndex

save

uid

setFeaturesCol

setPredictionCol

setFeatureIndex

boundaries

predictions

copy

transform

transformSchema

write

isotonic

getIsotonic

featureIndex

getFeatureIndex

hasWeightCol

extractWeightedLabeledPoints

validateAndTransformSchema