scalation/scalation/scalation.theory/Dataset

Dataset

scalation.theory.Dataset

case class Dataset(name: String, fileName: String, ncols: Int, xcols: Array[Int], ycol: Int)

The Dataset class supports loading data files (e.g., CSV files) and pre-processing them to create predictor/input matrices and response/output vectors. FIX -- extend to models that allow multiple responses/outputs (vector -> matrix).

Value parameters

fileName: the name of the file storing the dataset
name: the name of the dataset
xcols: the desired column numbers to take for predictors
ycol: the desired column number to take for the response

Attributes

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Supertypes: trait Serializable

trait Product

trait Equals

class Object

trait Matchable

class Any
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Members list

Value members

Concrete methods

Pre-process the raw data that may contain missing values, strings, dates, id columns, zero-variance columns, and outliers. Return the cleaned-up data.

Value parameters

tab: the table/linked-relation containing the raw data

Attributes

Show/print the table/linked-relation containing the data.

Value parameters

tab: the table/linked-relation containing the data

Attributes

Inherited methods

An iterator over the names of all the elements of this product.

Attributes

Inherited from:: Product

An iterator over all the elements of this product.

Attributes

Returns: in the default implementation, an Iterator[Any]
Inherited from:: Product

Concrete fields

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