RFormula (Spark 2.1.2 JavaDoc)

Object
- org.apache.spark.ml.PipelineStage
- - org.apache.spark.ml.Estimator<RFormulaModel>
  - - org.apache.spark.ml.feature.RFormula

All Implemented Interfaces:

java.io.Serializable, Params, DefaultParamsWritable, Identifiable, MLWritable
```
public class RFormula
extends Estimator<RFormulaModel>
implements DefaultParamsWritable
```
:: Experimental :: Implements the transforms required for fitting a dataset against an R model formula. Currently we support a limited subset of the R operators, including '~', '.', ':', '+', and '-'. Also see the R formula docs here: http://stat.ethz.ch/R-manual/R-patched/library/stats/html/formula.html
The basic operators are: - ~ separate target and terms - + concat terms, "+ 0" means removing intercept - - remove a term, "- 1" means removing intercept - : interaction (multiplication for numeric values, or binarized categorical values) - . all columns except target
Suppose a and b are double columns, we use the following simple examples to illustrate the effect of RFormula: - y ~ a + b means model y ~ w0 + w1 * a + w2 * b where w0 is the intercept and w1, w2 are coefficients. - y ~ a + b + a:b - 1 means model y ~ w1 * a + w2 * b + w3 * a * b where w1, w2, w3 are coefficients.
RFormula produces a vector column of features and a double or string column of label. Like when formulas are used in R for linear regression, string input columns will be one-hot encoded, and numeric columns will be cast to doubles. If the label column is of type string, it will be first transformed to double with StringIndexer. If the label column does not exist in the DataFrame, the output label column will be created from the specified response variable in the formula.

See Also:
Serialized Form

Constructor Summary

Constructors
Constructor and Description

RFormula()

RFormula(String uid)

Constructors
Constructor and Description
`RFormula()`
`RFormula(String uid)`

Method Summary

Methods
Modifier and Type	Method and Description
`static Params`	`clear(Param<?> param)`
`RFormula`	`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)`
`static Param<String>`	`featuresCol()`
`RFormulaModel`	`fit(Dataset<?> dataset)` Fits a model to the input data.
`BooleanParam`	`forceIndexLabel()` Force to index label whether it is numeric or string type.
`Param<String>`	`formula()` R formula parameter.
`static <T> scala.Option<T>`	`get(Param<T> param)`
`static <T> scala.Option<T>`	`getDefault(Param<T> param)`
`static String`	`getFeaturesCol()`
`boolean`	`getForceIndexLabel()`
`String`	`getFormula()`
`static String`	`getLabelCol()`
`static <T> T`	`getOrDefault(Param<T> param)`
`static Param<Object>`	`getParam(String paramName)`
`static <T> boolean`	`hasDefault(Param<T> param)`
`boolean`	`hasLabelCol(StructType schema)`
`static boolean`	`hasParam(String paramName)`
`static boolean`	`isDefined(Param<?> param)`
`static boolean`	`isSet(Param<?> param)`
`static Param<String>`	`labelCol()`
`static RFormula`	`load(String path)`
`static Param<?>[]`	`params()`
`static void`	`save(String path)`
`static <T> Params`	`set(Param<T> param, T value)`
`RFormula`	`setFeaturesCol(String value)`
`RFormula`	`setForceIndexLabel(boolean value)`
`RFormula`	`setFormula(String value)` Sets the formula to use for this transformer.
`RFormula`	`setLabelCol(String value)`
`String`	`toString()`
`StructType`	`transformSchema(StructType schema)` :: DeveloperApi ::
`String`	`uid()` An immutable unique ID for the object and its derivatives.
`static MLWriter`	`write()`

Methods inherited from class org.apache.spark.ml.Estimator
fit, fit, fit, fit

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

Methods inherited from interface org.apache.spark.ml.util.DefaultParamsWritable
write

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

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

- Constructor Detail
  - RFormula
```
public RFormula(String uid)
```
  - RFormula
```
public RFormula()
```
- Method Detail
  - load
```
public static RFormula load(String path)
```
  - 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()
```
  - 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()
```
  - save
```
public static void save(String path)
                 throws java.io.IOException
```
    Throws:
    
    java.io.IOException
  - write
```
public static MLWriter write()
```
  - 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)
  - formula
```
public Param<String> formula()
```
    R formula parameter. The formula is provided in string form.
    
    Returns:
    (undocumented)
  - setFormula
```
public RFormula setFormula(String value)
```
    Sets the formula to use for this transformer. Must be called before use.
    
    Parameters:
    value - an R formula in string form (e.g. "y ~ x + z")
    
    Returns:
    (undocumented)
  - getFormula
```
public String getFormula()
```
  - setFeaturesCol
```
public RFormula setFeaturesCol(String value)
```
  - setLabelCol
```
public RFormula setLabelCol(String value)
```
  - forceIndexLabel
```
public BooleanParam forceIndexLabel()
```
    Force to index label whether it is numeric or string type. Usually we index label only when it is string type. If the formula was used by classification algorithms, we can force to index label even it is numeric type by setting this param with true. Default: false.
    
    Returns:
    (undocumented)
  - getForceIndexLabel
```
public boolean getForceIndexLabel()
```
  - setForceIndexLabel
```
public RFormula setForceIndexLabel(boolean value)
```
  - fit
```
public RFormulaModel fit(Dataset<?> dataset)
```
    Description copied from class: Estimator
    
    Fits a model to the input data.
    
    Specified by:
    
    fit in class Estimator<RFormulaModel>
    
    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)
  - copy
```
public RFormula 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 Estimator<RFormulaModel>
    
    Parameters:
    extra - (undocumented)
    
    Returns:
    (undocumented)
  - toString
```
public String toString()
```
    Specified by:
    
    toString in interface Identifiable
    
    Overrides:
    
    toString in class Object
  - hasLabelCol
```
public boolean hasLabelCol(StructType schema)
```

Class RFormula

Constructor Summary

Method Summary

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

Methods inherited from class Object

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

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

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

Constructor Detail

RFormula

RFormula

Method Detail

load

params

explainParam

explainParams

isSet

isDefined

hasParam

getParam

set

get

clear

getOrDefault

getDefault

hasDefault

extractParamMap

extractParamMap

featuresCol

getFeaturesCol

labelCol

getLabelCol

save

write

uid

formula

setFormula

getFormula

setFeaturesCol

setLabelCol

forceIndexLabel

getForceIndexLabel

setForceIndexLabel

fit

transformSchema

copy

toString

hasLabelCol