Feature

Feature

id: (int) – the feature ID. (Note: Throughout the API, features are specified using their names, not this ID.)
name: (string) – feature name
projectId: (string) – the ID of the project the feature belongs to
featureType: (string) – feature type: ‘Numeric’, ‘Categorical’, etc.
importance: (float) – numeric measure of the strength of relationship between the feature and target (independent of any model or other features)
lowInformation: (bool) – whether feature has too few values to be informative
uniqueCount: (int) – number of unique values
naCount: (int) – number of missing values
dateFormat: (string)–(Newinversionv2.5)thedateformatstringforhowthisfeature was interpreted (or null if not a date feature). If not null, it will be compatible with https: //docs.python.org/2/library/time.html#time.strftime .
timeSeriesEligible: (bool) – (New in version v2.8) whether this feature can be used as a datetime partitioning feature for time series projects. Only sufficiently regular date features can be selected as the datetime feature for time series projects. Always false for non-date features. Date features that cannot be used in datetime partitioning for a time series project may be eligible for an OTV project, which has less stringent requirements.
timeSeriesEligibilityReason: (string)–(Newinversionv2.8)whythefeature is ineligible for time series projects, or “suitable” if it is eligible.
timeUnit: (string) – (New in version v2.8) the unit for the interval between values of this feature, e.g. DAY, MONTH, HOUR. When specifying windows for time series projects, the windows are expressed in terms of this unit. Only present for date features eligible for time series projects, and null otherwise.
timeStep: (int) – (New in version v2.8) The minimum time step that can be used to specify time series windows. The units for this value are the timeUnit. When specifying windows for time series projects, all windows must have durations that are integer multiples of this number. Only present for date features that are eligible for time series projects and null otherwise.
min: – minimum value of the EDA sample of the feature.
max: – maximum value of the EDA sample of the feature.
mean: – arithmetic mean of the EDA sample of the feature.
median: – median of the EDA sample of the feature.
stdDev: – standard deviation of EDA sample of the feature.
targetLeakage: (int) – whether or not the feature has target leakage. ‘SKIPPED_DETECTION’ indicates leakage detection was not run on the feature, ‘FALSE’ indicates no leakage, ‘MODERATE_RISK’ indicates a moderate risk of target leakage, and ‘HIGH_RISK’ indicates a high risk of target leakage

Linear Supertypes

Serializable, Serializable, Product, Equals, AnyRef, Any

Instance Constructors

new Feature(id: Option[String], name: Option[String], projectId: Option[String], featureType: Option[String], importance: Option[Double], lowInformation: Option[Boolean], uniqueCount: Option[Int], naCount: Option[Int], dateFormat: Option[String], timeSeriesEligible: Option[Boolean], timeSeriesEligibilityReason: Option[String], timeUnit: Option[String], timeStep: Option[Int], min: Option[Double], max: Option[Double], mean: Option[Double], median: Option[Double], stdDev: Option[Double], targetLeakage: Option[String])

id
(int) – the feature ID. (Note: Throughout the API, features are specified using their names, not this ID.)
name
(string) – feature name
projectId
(string) – the ID of the project the feature belongs to
featureType
(string) – feature type: ‘Numeric’, ‘Categorical’, etc.
importance
(float) – numeric measure of the strength of relationship between the feature and target (independent of any model or other features)
lowInformation
(bool) – whether feature has too few values to be informative
uniqueCount
(int) – number of unique values
naCount
(int) – number of missing values
dateFormat
(string)–(Newinversionv2.5)thedateformatstringforhowthisfeature was interpreted (or null if not a date feature). If not null, it will be compatible with https: //docs.python.org/2/library/time.html#time.strftime .
timeSeriesEligible
(bool) – (New in version v2.8) whether this feature can be used as a datetime partitioning feature for time series projects. Only sufficiently regular date features can be selected as the datetime feature for time series projects. Always false for non-date features. Date features that cannot be used in datetime partitioning for a time series project may be eligible for an OTV project, which has less stringent requirements.
timeSeriesEligibilityReason
(string)–(Newinversionv2.8)whythefeature is ineligible for time series projects, or “suitable” if it is eligible.
timeUnit
(string) – (New in version v2.8) the unit for the interval between values of this feature, e.g. DAY, MONTH, HOUR. When specifying windows for time series projects, the windows are expressed in terms of this unit. Only present for date features eligible for time series projects, and null otherwise.
timeStep
(int) – (New in version v2.8) The minimum time step that can be used to specify time series windows. The units for this value are the timeUnit. When specifying windows for time series projects, all windows must have durations that are integer multiples of this number. Only present for date features that are eligible for time series projects and null otherwise.
min
– minimum value of the EDA sample of the feature.
max
– maximum value of the EDA sample of the feature.
mean
– arithmetic mean of the EDA sample of the feature.
median
– median of the EDA sample of the feature.
stdDev
– standard deviation of EDA sample of the feature.
targetLeakage
(int) – whether or not the feature has target leakage. ‘SKIPPED_DETECTION’ indicates leakage detection was not run on the feature, ‘FALSE’ indicates no leakage, ‘MODERATE_RISK’ indicates a moderate risk of target leakage, and ‘HIGH_RISK’ indicates a high risk of target leakage

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
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@HotSpotIntrinsicCandidate() @throws( ... )
val dateFormat: Option[String]

(string)–(Newinversionv2.5)thedateformatstringforhowthisfeature was interpreted (or null if not a date feature).
(string)–(Newinversionv2.5)thedateformatstringforhowthisfeature was interpreted (or null if not a date feature). If not null, it will be compatible with https: //docs.python.org/2/library/time.html#time.strftime .
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
val featureType: Option[String]

(string) – feature type: ‘Numeric’, ‘Categorical’, etc.
final def getClass(): Class[_]

Definition Classes
AnyRef → Any
Annotations
@HotSpotIntrinsicCandidate()
def getFeatureHistogram()(implicit client: DataRobotClient): JValue
def getMetrics()(implicit client: DataRobotClient): Map[String, Any]
val id: Option[String]

(int) – the feature ID.
(int) – the feature ID. (Note: Throughout the API, features are specified using their names, not this ID.)
val importance: Option[Double]

(float) – numeric measure of the strength of relationship between the feature and target (independent of any model or other features)
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
val lowInformation: Option[Boolean]

(bool) – whether feature has too few values to be informative
val max: Option[Double]

– maximum value of the EDA sample of the feature.
val mean: Option[Double]

– arithmetic mean of the EDA sample of the feature.
val median: Option[Double]

– median of the EDA sample of the feature.
val min: Option[Double]

– minimum value of the EDA sample of the feature.
val naCount: Option[Int]

(int) – number of missing values
val name: Option[String]

(string) – feature name
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
Annotations
@HotSpotIntrinsicCandidate()
final def notifyAll(): Unit

Definition Classes
AnyRef
Annotations
@HotSpotIntrinsicCandidate()
val projectId: Option[String]

(string) – the ID of the project the feature belongs to
val stdDev: Option[Double]

– standard deviation of EDA sample of the feature.
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
val targetLeakage: Option[String]

(int) – whether or not the feature has target leakage.
(int) – whether or not the feature has target leakage. ‘SKIPPED_DETECTION’ indicates leakage detection was not run on the feature, ‘FALSE’ indicates no leakage, ‘MODERATE_RISK’ indicates a moderate risk of target leakage, and ‘HIGH_RISK’ indicates a high risk of target leakage
val timeSeriesEligibilityReason: Option[String]

(string)–(Newinversionv2.8)whythefeature is ineligible for time series projects, or “suitable” if it is eligible.
val timeSeriesEligible: Option[Boolean]

(bool) – (New in version v2.8) whether this feature can be used as a datetime partitioning feature for time series projects.
(bool) – (New in version v2.8) whether this feature can be used as a datetime partitioning feature for time series projects. Only sufficiently regular date features can be selected as the datetime feature for time series projects. Always false for non-date features. Date features that cannot be used in datetime partitioning for a time series project may be eligible for an OTV project, which has less stringent requirements.
val timeStep: Option[Int]

(int) – (New in version v2.8) The minimum time step that can be used to specify time series windows.
(int) – (New in version v2.8) The minimum time step that can be used to specify time series windows. The units for this value are the timeUnit. When specifying windows for time series projects, all windows must have durations that are integer multiples of this number. Only present for date features that are eligible for time series projects and null otherwise.
val timeUnit: Option[String]

(string) – (New in version v2.8) the unit for the interval between values of this feature, e.g.
(string) – (New in version v2.8) the unit for the interval between values of this feature, e.g. DAY, MONTH, HOUR. When specifying windows for time series projects, the windows are expressed in terms of this unit. Only present for date features eligible for time series projects, and null otherwise.
def toString(): String

Definition Classes
Feature → AnyRef → Any
val uniqueCount: Option[Int]

(int) – number of unique values
final def wait(arg0: Long, arg1: Int): Unit

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

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

Definition Classes
AnyRef
Annotations
@throws( ... )

Deprecated Value Members

def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@Deprecated @deprecated @throws( classOf[java.lang.Throwable] )
Deprecated
(Since version ) see corresponding Javadoc for more information.

Related Docs: object Feature | package datarobot

Instance Constructors

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

def clone(): AnyRef

val dateFormat: Option[String]

final def eq(arg0: AnyRef): Boolean

val featureType: Option[String]

final def getClass(): Class[_]

def getFeatureHistogram()(implicit client: DataRobotClient): JValue

def getMetrics()(implicit client: DataRobotClient): Map[String, Any]

val id: Option[String]

val importance: Option[Double]

final def isInstanceOf[T0]: Boolean

val lowInformation: Option[Boolean]

val max: Option[Double]

val mean: Option[Double]

val median: Option[Double]

val min: Option[Double]

val naCount: Option[Int]

val name: Option[String]

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

val projectId: Option[String]

val stdDev: Option[Double]

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

val targetLeakage: Option[String]

val timeSeriesEligibilityReason: Option[String]

val timeSeriesEligible: Option[Boolean]

val timeStep: Option[Int]

val timeUnit: Option[String]

def toString(): String

val uniqueCount: Option[Int]

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

final def wait(arg0: Long): Unit

final def wait(): Unit

Deprecated Value Members

def finalize(): Unit

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from AnyRef

Inherited from Any

Ungrouped