class FeatureSpec[T] extends AnyRef
Encapsulate specification for feature extraction and transformation.
- T
input record type to extract features from
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- FeatureSpec.scala
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def
compose[S](spec: FeatureSpec[S])(f: (T) ⇒ S): FeatureSpec[T]
Compose with another spec by applying a prepare function to input records first.
Compose with another spec by applying a prepare function to input records first.
Useful for reusing an existing spec for a different input record type.
- S
input record type of the other spec
- spec
spec to compose with
- f
function to prepare input records for the other spec
-
def
cross(k: (String, String))(f: (Double, Double) ⇒ Double): FeatureSpec[T]
Cross feature values of two underlying transformers.
Cross feature values of two underlying transformers.
- k
names of transformers to be crossed
- f
function to cross feature value pairs
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def
extract[M[_]](input: M[T])(implicit arg0: CollectionType[M]): FeatureExtractor[M, T]
Extract features from an input collection.
Extract features from an input collection.
This is done in two steps, a
reduce
step over the collection to aggregate feature summary, and amap
step to transform values using the summary.- M
input collection type, e.g.
Array
,List
- input
input collection
-
def
extractWithSettings[F](settings: String)(implicit arg0: FeatureBuilder[F], arg1: ClassTag[F]): RecordExtractor[T, F]
Extract features from individual records using settings from a previous session.
Extract features from individual records using settings from a previous session. Since the settings are parsed only once, this is more efficient and is recommended when the input is from an unbounded source, e.g. a stream of events or a backend service.
This bypasses the
reduce
step in extract and uses feature summary from settings exported in a previous session.- settings
JSON settings from a previous session
-
def
extractWithSettings[M[_]](input: M[T], settings: M[String])(implicit arg0: CollectionType[M]): FeatureExtractor[M, T]
Extract features from an input collection using settings from a previous session.
Extract features from an input collection using settings from a previous session.
This bypasses the
reduce
step in extract and uses feature summary from settings exported in a previous session.- M
input collection type, e.g.
Array
,List
- input
input collection
- settings
JSON settings from a previous session
-
def
extractWithSubsetSettings[F](settings: String)(implicit arg0: FeatureBuilder[F], arg1: ClassTag[F]): RecordExtractor[T, F]
Extract features from individual records using partial settings.
Extract features from individual records using partial settings. Since the settings are parsed only once, this is more efficient and is recommended when the input is from an unbounded source, e.g. a stream of events or a backend service.
This bypasses the
reduce
step in extract and uses feature summary from settings exported in a previous session.- settings
JSON settings from a previous session
-
def
extractWithSubsetSettings[M[_]](input: M[T], settings: M[String])(implicit arg0: CollectionType[M]): FeatureExtractor[M, T]
Extract features from an input collection using a partial settings from a previous session.
Extract features from an input collection using a partial settings from a previous session.
This bypasses the
reduce
step in extract and uses feature summary from settings exported in a previous session.- M
input collection type, e.g.
Array
,List
- input
input collection
- settings
JSON settings from a previous session
-
def
filter(predicate: (Feature[T, _, _, _]) ⇒ Boolean): FeatureSpec[T]
Creates a new FeatureSpec with only the features that respect the given predicate.
Creates a new FeatureSpec with only the features that respect the given predicate.
- predicate
Function determining whether or not to include the feature
-
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finalize(): Unit
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def
optional[A](f: (T) ⇒ Option[A], default: Option[A] = None)(t: Transformer[A, _, _]): FeatureSpec[T]
Add an optional field specification.
Add an optional field specification.
- A
extracted feature type
- f
function to extract feature
Option[A]
from recordT
- default
default for missing values
- t
Transformer for extracted feature
A
-
def
required[A](f: (T) ⇒ A)(t: Transformer[A, _, _]): FeatureSpec[T]
Add a required field specification.
Add a required field specification.
- A
extracted feature type
- f
function to extract feature
A
from recordT
- t
Transformer for extracted feature
A
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