CountVectorizerModel

Companion object CountVectorizerModel

class CountVectorizerModel extends Model[CountVectorizerModel] with CountVectorizerParams with MLWritable

Converts a text document to a sparse vector of token counts.

Annotations: @Since("1.5.0")
Source: CountVectorizer.scala

Linear Supertypes

MLWritable, CountVectorizerParams, HasOutputCol, HasInputCol, Model[CountVectorizerModel], Transformer, PipelineStage, Logging, Params, Serializable, Identifiable, AnyRef, Any

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CountVectorizerModel
MLWritable
CountVectorizerParams
HasOutputCol
HasInputCol
Model
Transformer
PipelineStage
Logging
Params
Serializable
Identifiable
AnyRef
Any

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Visibility

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Protected

Instance Constructors

new CountVectorizerModel(vocabulary: Array[String])
Annotations
@Since("1.5.0")
new CountVectorizerModel(uid: String, vocabulary: Array[String])
vocabulary
An Array over terms. Only the terms in the vocabulary will be counted.

Type Members

implicit class LogStringContext extends AnyRef
Definition Classes
Logging

Value Members

final def !=(arg0: Any): Boolean
Definition Classes
AnyRef → Any
final def ##: Int
Definition Classes
AnyRef → Any
final def $[T](param: Param[T]): T
An alias for getOrDefault().
An alias for getOrDefault().
Attributes
protected
Definition Classes
Params
final def ==(arg0: Any): Boolean
Definition Classes
AnyRef → Any
final def asInstanceOf[T0]: T0
Definition Classes
Any
val binary: BooleanParam
Binary toggle to control the output vector values.
Binary toggle to control the output vector values. If True, all nonzero counts (after minTF filter applied) are set to 1. This is useful for discrete probabilistic models that model binary events rather than integer counts. Default: false
Definition Classes
CountVectorizerParams
final def clear(param: Param[_]): CountVectorizerModel.this.type
Clears the user-supplied value for the input param.
Clears the user-supplied value for the input param.
Definition Classes
Params
def clone(): AnyRef
Attributes
protected[lang]
Definition Classes
AnyRef
Annotations
@throws(classOf[java.lang.CloneNotSupportedException]) @IntrinsicCandidate() @native()
def copy(extra: ParamMap): CountVectorizerModel
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
CountVectorizerModel → Model → Transformer → PipelineStage → Params
Annotations
@Since("1.5.0")
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
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
final def eq(arg0: AnyRef): Boolean
Definition Classes
AnyRef
def equals(arg0: AnyRef): Boolean
Definition Classes
AnyRef → Any
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
def explainParams(): String
Explains all params of this instance.
Explains all params of this instance. See explainParam().
Definition Classes
Params
final def extractParamMap(): ParamMap
extractParamMap with no extra values.
extractParamMap with no extra values.
Definition Classes
Params
final def extractParamMap(extra: ParamMap): 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
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
def getBinary: Boolean
Definition Classes
CountVectorizerParams
final def getClass(): Class[_ <: AnyRef]
Definition Classes
AnyRef → Any
Annotations
@IntrinsicCandidate() @native()
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
final def getInputCol: String
Definition Classes
HasInputCol
def getMaxDF: Double
Definition Classes
CountVectorizerParams
def getMinDF: Double
Definition Classes
CountVectorizerParams
def getMinTF: Double
Definition Classes
CountVectorizerParams
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
final def getOutputCol: String
Definition Classes
HasOutputCol
def getParam(paramName: String): Param[Any]
Gets a param by its name.
Gets a param by its name.
Definition Classes
Params
def getVocabSize: Int
Definition Classes
CountVectorizerParams
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
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
def hasParent: Boolean
Indicates whether this Model has a corresponding parent.
Indicates whether this Model has a corresponding parent.
Definition Classes
Model
def hashCode(): Int
Definition Classes
AnyRef → Any
Annotations
@IntrinsicCandidate() @native()
def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
Attributes
protected
Definition Classes
Logging
def initializeLogIfNecessary(isInterpreter: Boolean): Unit
Attributes
protected
Definition Classes
Logging
final val inputCol: Param[String]
Param for input column name.
Param for input column name.
Definition Classes
HasInputCol
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
final def isInstanceOf[T0]: Boolean
Definition Classes
Any
final def isSet(param: Param[_]): Boolean
Checks whether a param is explicitly set.
Checks whether a param is explicitly set.
Definition Classes
Params
def isTraceEnabled(): Boolean
Attributes
protected
Definition Classes
Logging
def log: Logger
Attributes
protected
Definition Classes
Logging
def logDebug(msg: => String, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logDebug(entry: LogEntry, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logDebug(entry: LogEntry): Unit
Attributes
protected
Definition Classes
Logging
def logDebug(msg: => String): Unit
Attributes
protected
Definition Classes
Logging
def logError(msg: => String, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logError(entry: LogEntry, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logError(entry: LogEntry): Unit
Attributes
protected
Definition Classes
Logging
def logError(msg: => String): Unit
Attributes
protected
Definition Classes
Logging
def logInfo(msg: => String, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logInfo(entry: LogEntry, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logInfo(entry: LogEntry): Unit
Attributes
protected
Definition Classes
Logging
def logInfo(msg: => String): Unit
Attributes
protected
Definition Classes
Logging
def logName: String
Attributes
protected
Definition Classes
Logging
def logTrace(msg: => String, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logTrace(entry: LogEntry, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logTrace(entry: LogEntry): Unit
Attributes
protected
Definition Classes
Logging
def logTrace(msg: => String): Unit
Attributes
protected
Definition Classes
Logging
def logWarning(msg: => String, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logWarning(entry: LogEntry, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logWarning(entry: LogEntry): Unit
Attributes
protected
Definition Classes
Logging
def logWarning(msg: => String): Unit
Attributes
protected
Definition Classes
Logging
val maxDF: DoubleParam
Specifies the maximum number of different documents a term could appear in to be included in the vocabulary.
Specifies the maximum number of different documents a term could appear in to be included in the vocabulary. A term that appears more than the threshold will be ignored. If this is an integer greater than or equal to 1, this specifies the maximum number of documents the term could appear in; if this is a double in [0,1), then this specifies the maximum fraction of documents the term could appear in.
Default: (2⁶³) - 1
Definition Classes
CountVectorizerParams
val minDF: DoubleParam
Specifies the minimum number of different documents a term must appear in to be included in the vocabulary.
Specifies the minimum number of different documents a term must appear in to be included in the vocabulary. If this is an integer greater than or equal to 1, this specifies the number of documents the term must appear in; if this is a double in [0,1), then this specifies the fraction of documents.
Default: 1.0
Definition Classes
CountVectorizerParams
val minTF: DoubleParam
Filter to ignore rare words in a document.
Filter to ignore rare words in a document. For each document, terms with frequency/count less than the given threshold are ignored. If this is an integer greater than or equal to 1, then this specifies a count (of times the term must appear in the document); if this is a double in [0,1), then this specifies a fraction (out of the document's token count).
Note that the parameter is only used in transform of CountVectorizerModel and does not affect fitting.
Default: 1.0
Definition Classes
CountVectorizerParams
final def ne(arg0: AnyRef): Boolean
Definition Classes
AnyRef
final def notify(): Unit
Definition Classes
AnyRef
Annotations
@IntrinsicCandidate() @native()
final def notifyAll(): Unit
Definition Classes
AnyRef
Annotations
@IntrinsicCandidate() @native()
final val outputCol: Param[String]
Param for output column name.
Param for output column name.
Definition Classes
HasOutputCol
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.
var parent: Estimator[CountVectorizerModel]
The parent estimator that produced this model.
The parent estimator that produced this model.
Definition Classes
Model
Note
For ensembles' component Models, this value can be null.
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("If the input path already exists but overwrite is not enabled.")
final def set(paramPair: ParamPair[_]): CountVectorizerModel.this.type
Sets a parameter in the embedded param map.
Sets a parameter in the embedded param map.
Attributes
protected
Definition Classes
Params
final def set(param: String, value: Any): CountVectorizerModel.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
final def set[T](param: Param[T], value: T): CountVectorizerModel.this.type
Sets a parameter in the embedded param map.
Sets a parameter in the embedded param map.
Definition Classes
Params
def setBinary(value: Boolean): CountVectorizerModel.this.type
Annotations
@Since("2.0.0")
final def setDefault(paramPairs: ParamPair[_]*): CountVectorizerModel.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
final def setDefault[T](param: Param[T], value: T): CountVectorizerModel.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[ml]
Definition Classes
Params
def setInputCol(value: String): CountVectorizerModel.this.type
Annotations
@Since("1.5.0")
def setMinTF(value: Double): CountVectorizerModel.this.type
Annotations
@Since("1.5.0")
def setOutputCol(value: String): CountVectorizerModel.this.type
Annotations
@Since("1.5.0")
def setParent(parent: Estimator[CountVectorizerModel]): CountVectorizerModel
Sets the parent of this model (Java API).
Sets the parent of this model (Java API).
Definition Classes
Model
final def synchronized[T0](arg0: => T0): T0
Definition Classes
AnyRef
def toString(): String
Definition Classes
CountVectorizerModel → Identifiable → AnyRef → Any
Annotations
@Since("3.0.0")
def transform(dataset: Dataset[_]): DataFrame
Transforms the input dataset.
Transforms the input dataset.
Definition Classes
CountVectorizerModel → Transformer
Annotations
@Since("2.0.0")
def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
Transforms the dataset with provided parameter map as additional parameters.
Transforms the dataset with provided parameter map as additional parameters.
dataset
input dataset
paramMap
additional parameters, overwrite embedded params
returns
transformed dataset
Definition Classes
Transformer
Annotations
@Since("2.0.0")
def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
Transforms the dataset with optional parameters
Transforms the dataset with optional parameters
dataset
input dataset
firstParamPair
the first param pair, overwrite embedded params
otherParamPairs
other param pairs, overwrite embedded params
returns
transformed dataset
Definition Classes
Transformer
Annotations
@Since("2.0.0") @varargs()
def transformSchema(schema: StructType): 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
CountVectorizerModel → PipelineStage
Annotations
@Since("1.5.0")
def transformSchema(schema: StructType, logging: Boolean): StructType
:: 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()
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
CountVectorizerModel → Identifiable
Annotations
@Since("1.5.0")
def validateAndTransformSchema(schema: StructType): StructType
Validates and transforms the input schema.
Validates and transforms the input schema.
Attributes
protected
Definition Classes
CountVectorizerParams
val vocabSize: IntParam
Max size of the vocabulary.
Max size of the vocabulary. CountVectorizer will build a vocabulary that only considers the top vocabSize terms ordered by term frequency across the corpus.
Default: 2¹⁸
Definition Classes
CountVectorizerParams
val vocabulary: Array[String]
Annotations
@Since("1.5.0")
final def wait(arg0: Long, arg1: Int): Unit
Definition Classes
AnyRef
Annotations
@throws(classOf[java.lang.InterruptedException])
final def wait(arg0: Long): Unit
Definition Classes
AnyRef
Annotations
@throws(classOf[java.lang.InterruptedException]) @native()
final def wait(): Unit
Definition Classes
AnyRef
Annotations
@throws(classOf[java.lang.InterruptedException])
def withLogContext(context: HashMap[String, String])(body: => Unit): Unit
Attributes
protected
Definition Classes
Logging
def write: MLWriter
Returns an MLWriter instance for this ML instance.
Returns an MLWriter instance for this ML instance.
Definition Classes
CountVectorizerModel → MLWritable
Annotations
@Since("1.6.0")

Deprecated Value Members

def finalize(): Unit
Attributes
protected[lang]
Definition Classes
AnyRef
Annotations
@throws(classOf[java.lang.Throwable]) @Deprecated
Deprecated
(Since version 9)

Inherited from MLWritable

Inherited from CountVectorizerParams

Inherited from HasOutputCol

Inherited from HasInputCol

Inherited from Model[CountVectorizerModel]

Inherited from Transformer

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

Parameters

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

Packages

Feature transformers

CountVectorizerModel

Companion object CountVectorizerModel

class CountVectorizerModel extends Model[CountVectorizerModel] with CountVectorizerParams with MLWritable

Instance Constructors

Type Members

Value Members

Deprecated Value Members

Inherited from MLWritable

Inherited from CountVectorizerParams

Inherited from HasOutputCol

Inherited from HasInputCol

Inherited from Model[CountVectorizerModel]

Inherited from Transformer

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

Parameters

Members

Parameter setters

Parameter getters

Packages

Feature transformers

CountVectorizerModel

Companion object CountVectorizerModel

class CountVectorizerModel extends Model[CountVectorizerModel] with CountVectorizerParams with MLWritable

Instance Constructors

Type Members

Value Members

Deprecated Value Members

Inherited from MLWritable

Inherited from CountVectorizerParams

Inherited from HasOutputCol

Inherited from HasInputCol

Inherited from Model[CountVectorizerModel]

Inherited from Transformer

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

Parameters

Members

Parameter setters

Parameter getters

CountVectorizerModel