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# RFormula 

### Companion object RFormula

#### class RFormula extends Estimator[RFormulaModel] with RFormulaBase with DefaultParamsWritable

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
• `*` factor crossing, includes the terms and interactions between them
• `^ factor crossing to a specified degree`

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.
• `y ~ a * b` means model `y ~ w0 + w1 * a + w2 * b + w3 * a * b` where `w0` is the intercept and `w1, w2, w3` are coefficients
• ```y ~ (a + b)^2 means model y ~ w0 + w1 * a + w2 * b + w3 * a * b where w0 is the intercept and 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.

Annotations
@Since( "1.5.0" )
Source
RFormula.scala
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Inherited
1. RFormula
2. DefaultParamsWritable
3. MLWritable
4. RFormulaBase
5. HasHandleInvalid
6. HasLabelCol
7. HasFeaturesCol
8. Estimator
9. PipelineStage
10. Logging
11. Params
12. Serializable
13. Serializable
14. Identifiable
15. AnyRef
16. Any
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Visibility
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2. All

### Instance Constructors

1. new RFormula()
Annotations
@Since( "1.5.0" )
2. new RFormula(uid: String)
Annotations
@Since( "1.5.0" )

### Value Members

1. final def !=(arg0: Any): Boolean
Definition Classes
AnyRef → Any
2. final def ##(): Int
Definition Classes
AnyRef → Any
3. final def \$[T](param: Param[T]): T

An alias for `getOrDefault()`.

An alias for `getOrDefault()`.

Attributes
protected
Definition Classes
Params
4. final def ==(arg0: Any): Boolean
Definition Classes
AnyRef → Any
5. final def asInstanceOf[T0]: T0
Definition Classes
Any
6. final def clear(param: Param[_]): RFormula.this.type

Clears the user-supplied value for the input param.

Clears the user-supplied value for the input param.

Definition Classes
Params
7. def clone(): AnyRef
Attributes
protected[lang]
Definition Classes
AnyRef
Annotations
@throws( ... ) @native()
8. def copy(extra: ParamMap)

Creates a copy of this instance with the same UID and some extra 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()`.

Definition Classes
RFormulaEstimatorPipelineStageParams
Annotations
@Since( "1.5.0" )
9. def copyValues[T <: Params](to: T, extra: ParamMap = ParamMap.empty): T

Copies param values from this instance to another instance for params shared by them.

Copies param values from this instance to another instance for params shared by them.

This handles default Params and explicitly set Params separately. Default Params are copied from and to `defaultParamMap`, and explicitly set Params are copied from and to `paramMap`. Warning: This implicitly assumes that this Params instance and the target instance share the same set of default Params.

to

the target instance, which should work with the same set of default Params as this source instance

extra

extra params to be copied to the target's `paramMap`

returns

the target instance with param values copied

Attributes
protected
Definition Classes
Params
10. final def defaultCopy[T <: Params](extra: ParamMap): T

Default implementation of copy with extra params.

Default implementation of copy with extra params. It tries to create a new instance with the same UID. Then it copies the embedded and extra parameters over and returns the new instance.

Attributes
protected
Definition Classes
Params
11. final def eq(arg0: AnyRef): Boolean
Definition Classes
AnyRef
12. def equals(arg0: Any): Boolean
Definition Classes
AnyRef → Any
13. def explainParam(param: Param[_]): String

Explains a param.

Explains a param.

param

input param, must belong to this instance.

returns

a string that contains the input param name, doc, and optionally its default value and the user-supplied value

Definition Classes
Params
14. def explainParams(): String

Explains all params of this instance.

Explains all params of this instance. See `explainParam()`.

Definition Classes
Params
15. final def extractParamMap()

`extractParamMap` with no extra values.

`extractParamMap` with no extra values.

Definition Classes
Params
16. final def extractParamMap(extra: ParamMap)

Extracts the embedded default param values and user-supplied values, and then merges them with extra values from input into a flat param map, where the latter value is used if there exist conflicts, i.e., with ordering: default param values less than user-supplied values less than extra.

Extracts the embedded default param values and user-supplied values, and then merges them with extra values from input into a flat param map, where the latter value is used if there exist conflicts, i.e., with ordering: default param values less than user-supplied values less than extra.

Definition Classes
Params
17. final val featuresCol: Param[String]

Param for features column name.

Param for features column name.

Definition Classes
HasFeaturesCol
18. def finalize(): Unit
Attributes
protected[lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
19. def fit(dataset: Dataset[_])

Fits a model to the input data.

Fits a model to the input data.

Definition Classes
RFormulaEstimator
Annotations
@Since( "2.0.0" )
20. def fit(dataset: Dataset[_], paramMaps: Seq[ParamMap]): Seq[RFormulaModel]

Fits multiple models to the input data with multiple sets of parameters.

Fits multiple models to the input data with multiple sets of parameters. The default implementation uses a for loop on each parameter map. Subclasses could override this to optimize multi-model training.

dataset

input dataset

paramMaps

An array of parameter maps. These values override any specified in this Estimator's embedded ParamMap.

returns

fitted models, matching the input parameter maps

Definition Classes
Estimator
Annotations
@Since( "2.0.0" )
21. def fit(dataset: Dataset[_], paramMap: ParamMap)

Fits a single model to the input data with provided parameter map.

Fits a single model to the input data with provided parameter map.

dataset

input dataset

paramMap

Parameter map. These values override any specified in this Estimator's embedded ParamMap.

returns

fitted model

Definition Classes
Estimator
Annotations
@Since( "2.0.0" )
22. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*)

Fits a single model to the input data with optional parameters.

Fits a single model to the input data with optional parameters.

dataset

input dataset

firstParamPair

the first param pair, overrides embedded params

otherParamPairs

other param pairs. These values override any specified in this Estimator's embedded ParamMap.

returns

fitted model

Definition Classes
Estimator
Annotations
@Since( "2.0.0" ) @varargs()
23. val forceIndexLabel

Force to index label whether it is numeric or string type.

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.

Definition Classes
RFormulaBase
Annotations
@Since( "2.1.0" )
24. val formula: Param[String]

R formula parameter.

R formula parameter. The formula is provided in string form.

Definition Classes
RFormulaBase
Annotations
@Since( "1.5.0" )
25. final def get[T](param: Param[T]): Option[T]

Optionally returns the user-supplied value of a param.

Optionally returns the user-supplied value of a param.

Definition Classes
Params
26. final def getClass(): Class[_]
Definition Classes
AnyRef → Any
Annotations
@native()
27. final def getDefault[T](param: Param[T]): Option[T]

Gets the default value of a parameter.

Gets the default value of a parameter.

Definition Classes
Params
28. final def getFeaturesCol: String

Definition Classes
HasFeaturesCol
29. def getForceIndexLabel: Boolean

Definition Classes
RFormulaBase
Annotations
@Since( "2.1.0" )
30. def getFormula: String

Definition Classes
RFormulaBase
Annotations
@Since( "1.5.0" )
31. final def getHandleInvalid: String

Definition Classes
HasHandleInvalid
32. final def getLabelCol: String

Definition Classes
HasLabelCol
33. final def getOrDefault[T](param: Param[T]): T

Gets the value of a param in the embedded param map or its default value.

Gets the value of a param in the embedded param map or its default value. Throws an exception if neither is set.

Definition Classes
Params
34. def getParam(paramName: String): Param[Any]

Gets a param by its name.

Gets a param by its name.

Definition Classes
Params
35. def getStringIndexerOrderType: String

Definition Classes
RFormulaBase
Annotations
@Since( "2.3.0" )
36. val handleInvalid: Param[String]

Param for how to handle invalid data (unseen or NULL values) in features and label column of string type.

Param for how to handle invalid data (unseen or NULL values) in features and label column of string type. Options are 'skip' (filter out rows with invalid data), 'error' (throw an error), or 'keep' (put invalid data in a special additional bucket, at index numLabels). Default: "error"

Definition Classes
RFormulaBase → HasHandleInvalid
Annotations
@Since( "2.3.0" )
37. final def hasDefault[T](param: Param[T]): Boolean

Tests whether the input param has a default value set.

Tests whether the input param has a default value set.

Definition Classes
Params
38. def hasLabelCol(schema: StructType): Boolean
Attributes
protected
Definition Classes
RFormulaBase
39. def hasParam(paramName: String): Boolean

Tests whether this instance contains a param with a given name.

Tests whether this instance contains a param with a given name.

Definition Classes
Params
40. def hashCode(): Int
Definition Classes
AnyRef → Any
Annotations
@native()
41. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
Attributes
protected
Definition Classes
Logging
42. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
Attributes
protected
Definition Classes
Logging
43. final def isDefined(param: Param[_]): Boolean

Checks whether a param is explicitly set or has a default value.

Checks whether a param is explicitly set or has a default value.

Definition Classes
Params
44. final def isInstanceOf[T0]: Boolean
Definition Classes
Any
45. final def isSet(param: Param[_]): Boolean

Checks whether a param is explicitly set.

Checks whether a param is explicitly set.

Definition Classes
Params
46. def isTraceEnabled(): Boolean
Attributes
protected
Definition Classes
Logging
47. final val labelCol: Param[String]

Param for label column name.

Param for label column name.

Definition Classes
HasLabelCol
48. def log: Logger
Attributes
protected
Definition Classes
Logging
49. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
50. def logDebug(msg: ⇒ String): Unit
Attributes
protected
Definition Classes
Logging
51. def logError(msg: ⇒ String, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
52. def logError(msg: ⇒ String): Unit
Attributes
protected
Definition Classes
Logging
53. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
54. def logInfo(msg: ⇒ String): Unit
Attributes
protected
Definition Classes
Logging
55. def logName: String
Attributes
protected
Definition Classes
Logging
56. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
57. def logTrace(msg: ⇒ String): Unit
Attributes
protected
Definition Classes
Logging
58. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
59. def logWarning(msg: ⇒ String): Unit
Attributes
protected
Definition Classes
Logging
60. final def ne(arg0: AnyRef): Boolean
Definition Classes
AnyRef
61. final def notify(): Unit
Definition Classes
AnyRef
Annotations
@native()
62. final def notifyAll(): Unit
Definition Classes
AnyRef
Annotations
@native()
63. lazy val params: Array[Param[_]]

Returns all params sorted by their names.

Returns all params sorted by their names. The default implementation uses Java reflection to list all public methods that have no arguments and return Param.

Definition Classes
Params
Note

Developer should not use this method in constructor because we cannot guarantee that this variable gets initialized before other params.

64. def save(path: String): Unit

Saves this ML instance to the input path, a shortcut of `write.save(path)`.

Saves this ML instance to the input path, a shortcut of `write.save(path)`.

Definition Classes
MLWritable
Annotations
@Since( "1.6.0" ) @throws( ... )
65. final def set(paramPair: ParamPair[_]): RFormula.this.type

Sets a parameter in the embedded param map.

Sets a parameter in the embedded param map.

Attributes
protected
Definition Classes
Params
66. final def set(param: String, value: Any): RFormula.this.type

Sets a parameter (by name) in the embedded param map.

Sets a parameter (by name) in the embedded param map.

Attributes
protected
Definition Classes
Params
67. final def set[T](param: Param[T], value: T): RFormula.this.type

Sets a parameter in the embedded param map.

Sets a parameter in the embedded param map.

Definition Classes
Params
68. final def setDefault(paramPairs: ParamPair[_]*): RFormula.this.type

Sets default values for a list of params.

Sets default values for a list of params.

Note: Java developers should use the single-parameter `setDefault`. Annotating this with varargs can cause compilation failures due to a Scala compiler bug. See SPARK-9268.

paramPairs

a list of param pairs that specify params and their default values to set respectively. Make sure that the params are initialized before this method gets called.

Attributes
protected
Definition Classes
Params
69. final def setDefault[T](param: Param[T], value: T): RFormula.this.type

Sets a default value for a param.

Sets a default value for a param.

param

param to set the default value. Make sure that this param is initialized before this method gets called.

value

the default value

Attributes
protected
Definition Classes
Params
70. def setFeaturesCol(value: String): RFormula.this.type

Annotations
@Since( "1.5.0" )
71. def setForceIndexLabel(value: Boolean): RFormula.this.type

Annotations
@Since( "2.1.0" )
72. def setFormula(value: String): RFormula.this.type

Sets the formula to use for this transformer.

Sets the formula to use for this transformer. Must be called before use.

value

an R formula in string form (e.g. "y ~ x + z")

Annotations
@Since( "1.5.0" )
73. def setHandleInvalid(value: String): RFormula.this.type

Annotations
@Since( "2.3.0" )
74. def setLabelCol(value: String): RFormula.this.type

Annotations
@Since( "1.5.0" )
75. def setStringIndexerOrderType(value: String): RFormula.this.type

Annotations
@Since( "2.3.0" )
76. final val stringIndexerOrderType: Param[String]

Param for how to order categories of a string FEATURE column used by `StringIndexer`.

Param for how to order categories of a string FEATURE column used by `StringIndexer`. The last category after ordering is dropped when encoding strings. Supported options: 'frequencyDesc', 'frequencyAsc', 'alphabetDesc', 'alphabetAsc'. The default value is 'frequencyDesc'. When the ordering is set to 'alphabetDesc', `RFormula` drops the same category as R when encoding strings.

The options are explained using an example `'b', 'a', 'b', 'a', 'c', 'b'`:

```+-----------------+---------------------------------------+----------------------------------+
|      Option     | Category mapped to 0 by StringIndexer |  Category dropped by RFormula    |
+-----------------+---------------------------------------+----------------------------------+
| 'frequencyDesc' | most frequent category ('b')          | least frequent category ('c')    |
| 'frequencyAsc'  | least frequent category ('c')         | most frequent category ('b')     |
| 'alphabetDesc'  | last alphabetical category ('c')      | first alphabetical category ('a')|
| 'alphabetAsc'   | first alphabetical category ('a')     | last alphabetical category ('c') |
+-----------------+---------------------------------------+----------------------------------+```

Note that this ordering option is NOT used for the label column. When the label column is indexed, it uses the default descending frequency ordering in `StringIndexer`.

Definition Classes
RFormulaBase
Annotations
@Since( "2.3.0" )
77. final def synchronized[T0](arg0: ⇒ T0): T0
Definition Classes
AnyRef
78. def toString(): String
Definition Classes
RFormulaIdentifiable → AnyRef → Any
Annotations
@Since( "2.0.0" )
79. def transformSchema(schema: StructType)

Check transform validity and derive the output schema from the input schema.

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.

Definition Classes
RFormulaPipelineStage
Annotations
@Since( "1.5.0" )
80. def transformSchema(schema: StructType, logging: Boolean)

:: DeveloperApi ::

:: DeveloperApi ::

Derives the output schema from the input schema and parameters, optionally with logging.

This should be optimistic. If it is unclear whether the schema will be valid, then it should be assumed valid until proven otherwise.

Attributes
protected
Definition Classes
PipelineStage
Annotations
@DeveloperApi()
81. val uid: String

An immutable unique ID for the object and its derivatives.

An immutable unique ID for the object and its derivatives.

Definition Classes
RFormulaIdentifiable
Annotations
@Since( "1.5.0" )
82. final def wait(): Unit
Definition Classes
AnyRef
Annotations
@throws( ... )
83. final def wait(arg0: Long, arg1: Int): Unit
Definition Classes
AnyRef
Annotations
@throws( ... )
84. final def wait(arg0: Long): Unit
Definition Classes
AnyRef
Annotations
@throws( ... ) @native()
85. def write

Returns an `MLWriter` instance for this ML instance.

Returns an `MLWriter` instance for this ML instance.

Definition Classes
DefaultParamsWritableMLWritable

### Parameters

A list of (hyper-)parameter keys this algorithm can take. Users can set and get the parameter values through setters and getters, respectively.