class
Evaluator extends AnyRef
Instance Constructors
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new
Evaluator()
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new
Evaluator(opts: MEOptions)
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Value Members
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final
def
!=(arg0: Any): Boolean
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final
def
##(): Int
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final
def
==(arg0: Any): Boolean
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def
accuracy(m: Array[Array[Int]]): Double
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def
addJInstance(l: String, fs: List[String]): Unit
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def
addTo(m1: Array[Array[Int]], m2: Array[Array[Int]]): Unit
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final
def
asInstanceOf[T0]: T0
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def
clone(): AnyRef
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def
colSum(m: Array[Array[Int]], i: Int): Int
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val
decodedOutputStream: Option[OutputStreamWriter]
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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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final
def
getClass(): Class[_]
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def
getConfusionMatrix(s: Int, pairs: Seq[(Int, Int)]): Array[Array[Int]]
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def
getLabel(i: Int, invMap: Map[Int, AbstractLabel]): String
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def
hashCode(): Int
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final
def
isInstanceOf[T0]: Boolean
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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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def
precision(m: Array[Array[Int]], i: Int): Double
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def
produceReport(confMatsAndDivergence: IndexedSeq[(Array[Array[Int]], Double)], nfolds: Int, f: File): Unit
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def
recall(m: Array[Array[Int]], i: Int): Double
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def
reportOnMatrix(xval: Boolean, fname: String, os: Writer, mat: Array[Array[Int]]): Unit
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def
rowSum(m: Array[Array[Int]], i: Int): Int
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def
setInstances: Unit
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def
setSources: Unit
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final
def
synchronized[T0](arg0: ⇒ T0): T0
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def
toString(): String
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def
trainAndEvaluate(training: Seq[ObsSource[List[(FeatureId, Double)]]], testing: Seq[ObsSource[List[(FeatureId, Double)]]]): (Array[Array[Int]], Double)
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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
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def
xValidate(n: Int): IndexedSeq[(Array[Array[Int]], Double)]
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def
xValidateAndGenerateReport(nfolds: Int, f: File): Unit
Inherited from AnyRef
Inherited from Any