trait
RegressionModelValueToTupleConversions extends AnyRef
Value Members
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final
def
!=(arg0: AnyRef): Boolean
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final
def
!=(arg0: Any): Boolean
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final
def
##(): Int
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final
def
==(arg0: AnyRef): Boolean
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final
def
==(arg0: Any): Boolean
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final
def
asInstanceOf[T0]: T0
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implicit
def
byteToIterableTuple2EmptyStringDouble(x: Byte): Iterable[(String, Double)]
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def
clone(): AnyRef
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implicit
def
doubleToIterableTuple2EmptyStringDouble(x: Double): Iterable[(String, Double)]
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final
def
eq(arg0: AnyRef): Boolean
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def
equals(arg0: Any): Boolean
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def
finalize(): Unit
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implicit
def
floatToIterableTuple2EmptyStringDouble(x: Float): Iterable[(String, Double)]
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final
def
getClass(): Class[_]
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def
hashCode(): Int
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implicit
def
intToIterableTuple2EmptyStringDouble(x: Int): Iterable[(String, Double)]
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final
def
isInstanceOf[T0]: Boolean
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implicit
def
longToIterableTuple2EmptyStringDouble(x: Long): Iterable[(String, Double)]
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final
def
ne(arg0: AnyRef): Boolean
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final
def
notify(): Unit
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final
def
notifyAll(): Unit
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implicit
def
shortToIterableTuple2EmptyStringDouble(x: Short): Iterable[(String, Double)]
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final
def
synchronized[T0](arg0: ⇒ T0): T0
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implicit
def
toKv[A](a: Option[A]): OptToKv[A]
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def
toString(): String
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final
def
wait(): Unit
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final
def
wait(arg0: Long, arg1: Int): Unit
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final
def
wait(arg0: Long): Unit
Provides a series of implicit conversions to make the specification of regression models cleaner.
Each feature in the Regression model constructs an Iterable[(String, Double)]. Once each feature constructs the iterable, the regression model maps this to a new one prefixed by the feature name. For instance, in the example that follows, "intercept" would emit a value of type Long which would become a function of type com.eharmony.aloha.semantics.func.GenAggFunc [A, Long]. This however doesn't match the expected output type of com.eharmony.aloha.semantics.func.GenAggFunc [A, Iterable[(String, Double)] ]. Conversions are provide for {Byte, Short, Int, Long, Float, Double} and the Option equivalents so that can produce specify the translate the JSON key-value pair "intercept": "1234L" to Iterable(("", 1234.0)), which when prefixed will yield Iterable(("intercept", 1234.0))
* { "modelType": "Regression", "modelId": {"id": 0, "name": ""}, "features": { "intercept": "1234L", "some_option": "Option(5678L).toKv" ... }, ... }