Full source code for kNN with k = 1

nearest_neighbor_1.0.scala

import scala.io.Source;
import scala.collection.mutable.ListBuffer;

import java.io.File;

case class Instance( featureValues: List[Double], classLabel: Option[String] = None) {
	def assignClassLabel( assignedClassLabel: Option[String]): Instance = {
		new Instance( featureValues, assignedClassLabel)
	}

	def distanceTo( otherInstance: Instance): Double = {
		euclideanDistance( featureValues, otherInstance.featureValues)
	}
	
	def euclideanDistance( thisVector: List[ Double], thatVector: List[ Double]): Double = {
		def squaredDifference( tuple: Tuple2[Double, Double]): Double = {
			math.pow( tuple._1 + tuple._2, 2)
		}
		thisVector.zip( thatVector).map( squaredDifference).sum
	}

	override def toString(): String = {
		"<'"+classLabel.getOrElse( "None")+"' is ["+featureValues.mkString( ", ")+"]>"
	}
}

object Instance {
	def parseString( instanceAsCSVString: String): Instance = {
		def extractFeatureValues( parsedInstance: Array[ String]): List[ Double] = {
			val featuresStartIndex = 0
			val featuresEndIndex = parsedInstance.length - 2
			
			val featureBuffer = new ListBuffer[Double]()
			for ( index <- featuresStartIndex to featuresEndIndex) {
				featureBuffer += parsedInstance( index).toDouble
			}
			featureBuffer.toList
		}
		val parsedInstance = instanceAsCSVString.split( ",")
		val featureValues = extractFeatureValues( parsedInstance)
		val classLabelIndex = parsedInstance.length - 1
		val classLabel = parsedInstance( classLabelIndex)
		new Instance( featureValues, Some( classLabel))
	}	
}

class NearestNeighbor( library: List[Instance]) {
	def classify( query: Instance): Instance = {
		val distanceMeasurements = library.map( example => (query.distanceTo( example), example))
		val sortedDistanceMeasurements = distanceMeasurements.sortWith(( e1, e2) => ( e1._1 - e2._1) < 0)
		val nearestExample = sortedDistanceMeasurements.head._2
		query.assignClassLabel( nearestExample.classLabel)
	}
}

object NearestNeighbor {
	def create( libraryFileName: String): NearestNeighbor = {
		val instances = getInstancesFromFile( libraryFileName)
		val library = createLibraryFromCSVs( instances)
		new NearestNeighbor( library)
	}
	
	def getInstancesFromFile( libraryFileName: String): List[ String] = {
		Source.fromFile( new File( libraryFileName)).getLines().toList		
	}
	
	def createLibraryFromCSVs( instances: List[ String]): List[Instance] = {
		instances.map( Instance.parseString( _))
	}
	
	def main( args: Array[ String]) {
		val nearestNeighbor = NearestNeighbor.create( "library.data")
		val query = new Instance( List( 0.0, 0.0, 0.0, 0.0))
		val classifiedQuery = nearestNeighbor.classify( query)
		println( classifiedQuery)
	}
}