DataRef

Instance Constructors

new DataRef(id: String, path: String, header: Int, separator: String, category: String, excludeIndex: Boolean = false)

Value Members

final def !=(arg0: Any): Boolean

Definition Classes
AnyRef → Any
final def ##(): Int

Definition Classes
AnyRef → Any
final def ==(arg0: Any): Boolean

Definition Classes
AnyRef → Any
final def asInstanceOf[T0]: T0

Definition Classes
Any
val category: String
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
val excludeIndex: Boolean
def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
final def getClass(): Class[_]

Definition Classes
AnyRef → Any
def getLabels: Array[Boolean]

Return the labels of a data set
Return the labels of a data set
returns
An array of boolean (only boolean labels are supported currently)
val header: Int
val id: String
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
final def notifyAll(): Unit

Definition Classes
AnyRef
def open(dropClass: Boolean = true, max1000: Boolean = false): Array[Array[Double]]

Open the data ref
Open the data ref
dropClass
Whether to drop the "class" column if there is one. (assumes it is the last one)
max1000
cap the opened data to 1000 rows. If the original data has more rows, sample 1000 without replacement
returns
A 2-D Array of Double containing the values from the csv. (row oriented)
def openAndPreprocess(test: Stats, dropClass: Boolean = true, max1000: Boolean = false): PreprocessedData

Open the data ref and preprocess it according to a specific statistical test
Open the data ref and preprocess it according to a specific statistical test
dropClass
Whether to drop the "class" column if there is one. (assumes it is the last one)
max1000
cap the opened data to 1000 rows. If the original data has more rows, sample 1000 without replacement
returns
A 2-D Array of Double containing the values from the csv, preprocessed. (column oriented)
val path: String
val separator: String
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
final def wait(): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long, arg1: Int): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )

Related Doc: package preprocess

case class DataRef(id: String, path: String, header: Int, separator: String, category: String, excludeIndex: Boolean = false) extends Product with Serializable

Instance Constructors

new DataRef(id: String, path: String, header: Int, separator: String, category: String, excludeIndex: Boolean = false)

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

val category: String

def clone(): AnyRef

final def eq(arg0: AnyRef): Boolean

val excludeIndex: Boolean

def finalize(): Unit

final def getClass(): Class[_]

def getLabels: Array[Boolean]

val header: Int

val id: String

final def isInstanceOf[T0]: Boolean

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

def open(dropClass: Boolean = true, max1000: Boolean = false): Array[Array[Double]]

def openAndPreprocess(test: Stats, dropClass: Boolean = true, max1000: Boolean = false): PreprocessedData

val path: String

val separator: String

final def synchronized[T0](arg0: ⇒ T0): T0

final def wait(): Unit

final def wait(arg0: Long, arg1: Int): Unit

final def wait(arg0: Long): Unit

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from AnyRef

Inherited from Any

Ungrouped