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org.pmml4s.xml.NearestNeighborBuilder.scala Maven / Gradle / Ivy
/*
* Copyright (c) 2017-2023 AutoDeployAI
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.pmml4s.xml
import org.pmml4s.common.{CompareFunction, ComparisonMeasure, Table}
import org.pmml4s.model._
/**
* Builder of Nearest Neighbor model.
*/
class NearestNeighborBuilder extends Builder[NearestNeighborModel] {
protected var attributes: NearestNeighborAttributes = _
private var trainingInstances: TrainingInstances = _
private var comparisonMeasure: ComparisonMeasure = _
private var knnInputs: KNNInputs = _
/** Builds a PMML model from a specified XML reader. */
override def build(reader: XMLEventReader, attrs: XmlAttrs, parent: Model): NearestNeighborModel = {
this.parent = parent
this.attributes = makeAttributes(attrs)
traverseModel(reader, name, {
case EvElemStart(_, ElemTags.TRAINING_INSTANCES, attrs, _) =>
trainingInstances = makeTrainingInstances(reader, attrs)
case EvElemStart(_, ElemTags.COMPARISON_MEASURE, attrs, _) =>
comparisonMeasure = makeComparisonMeasure(reader, attrs)
case EvElemStart(_, ElemTags.KNN_INPUTS, attrs, _) =>
knnInputs = makeKNNInputs(reader, attrs)
})
new NearestNeighborModel(parent, attributes, miningSchema,
trainingInstances, comparisonMeasure, knnInputs,
output, targets, localTransformations, modelStats, modelExplanation, modelVerification, extensions.toIndexedSeq)
}
def makeTrainingInstances(reader: XMLEventReader, attrs: XmlAttrs): TrainingInstances = makeElem(reader, attrs,
new ElemBuilder[TrainingInstances] {
override def build(reader: XMLEventReader, attrs: XmlAttrs): TrainingInstances = {
val isTransformed = attrs.getBoolean(AttrTags.IS_TRANSFORMED, false)
val recordCount = attrs.getInt(AttrTags.RECORD_COUNT)
val fieldCount = attrs.getInt(AttrTags.FIELD_COUNT)
var instanceFields: InstanceFields = null
var table: Table = null
traverseElems(reader, ElemTags.TRAINING_INSTANCES, {
case EvElemStart(_, ElemTags.INSTANCE_FIELDS, attrs, _) => instanceFields =
makeElem(reader, attrs, new ElemBuilder[InstanceFields] {
override def build(reader: XMLEventReader, attrs: XmlAttrs): InstanceFields = {
val instanceFields = makeElems(reader, ElemTags.INSTANCE_FIELDS, ElemTags.INSTANCE_FIELD,
new ElemBuilder[InstanceField] {
override def build(reader: XMLEventReader, attrs: XmlAttrs): InstanceField = {
val field = attrs(AttrTags.FIELD)
val column = attrs.get(AttrTags.COLUMN)
new InstanceField(field, column)
}
})
new InstanceFields(instanceFields)
}
})
case event: EvElemStart if Table.contains(event.label) => table = makeTable(reader, event)
})
new TrainingInstances(instanceFields, table, isTransformed, recordCount, fieldCount)
}
})
def makeKNNInputs(reader: XMLEventReader, attrs: XmlAttrs): KNNInputs = makeElem(reader, attrs,
new ElemBuilder[KNNInputs] {
override def build(reader: XMLEventReader, attrs: XmlAttrs): KNNInputs = {
val knnInputs = makeElems(reader, ElemTags.KNN_INPUTS, ElemTags.KNN_INPUT, new ElemBuilder[KNNInput] {
override def build(reader: XMLEventReader, attrs: XmlAttrs): KNNInput = {
val f = field(attrs(AttrTags.FIELD))
val fieldWeight = attrs.getDouble(AttrTags.FIELD_WEIGHT, 1.0)
val compareFunction = attrs.get(AttrTags.COMPARE_FUNCTION).map(CompareFunction.withName(_))
new KNNInput(f, compareFunction, fieldWeight)
}
})
new KNNInputs(knnInputs)
}
})
/** Extracts these common attributes from a model */
override protected def makeAttributes(attrs: XmlAttrs): NearestNeighborAttributes = {
val attributes = super.makeAttributes(attrs)
new NearestNeighborAttributes(
functionName = attributes.functionName,
modelName = attributes.modelName,
algorithmName = attributes.algorithmName,
isScorable = attributes.isScorable,
numberOfNeighbors = attrs.int(AttrTags.NUMBER_OF_NEIGHBORS),
continuousScoringMethod = attrs.get(AttrTags.CONTINUOUS_SCORING_METHOD).map(x => ContScoringMethod.withName(x)).
getOrElse(ContScoringMethod.average),
categoricalScoringMethod = attrs.get(AttrTags.CATEGORICAL_SCORING_METHOD).map(x => CatScoringMethod.withName(x)).
getOrElse(CatScoringMethod.majorityVote),
instanceIdVariable = attrs.get(AttrTags.INSTANCE_ID_VARIABLE),
threshold = attrs.getDouble(AttrTags.THRESHOLD, 0.001)
)
}
/** Name of the builder. */
override def name: String = ElemTags.NEAREST_NEIGHBOR_MODEL
}