one feature

This commit is contained in:
Joe Darby
2016-12-16 13:04:57 +00:00
parent d5098b84a5
commit 2eaeb5584c
7 changed files with 69 additions and 13 deletions
+26
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@@ -0,0 +1,26 @@
<?xml version="1.0" encoding="UTF-8"?>
<classpath>
<classpathentry kind="src" output="target/classes" path="src/main/java">
<attributes>
<attribute name="optional" value="true"/>
<attribute name="maven.pomderived" value="true"/>
</attributes>
</classpathentry>
<classpathentry kind="src" output="target/test-classes" path="src/test/java">
<attributes>
<attribute name="optional" value="true"/>
<attribute name="maven.pomderived" value="true"/>
</attributes>
</classpathentry>
<classpathentry kind="con" path="org.eclipse.jdt.launching.JRE_CONTAINER/org.eclipse.jdt.internal.debug.ui.launcher.StandardVMType/JavaSE-1.6">
<attributes>
<attribute name="maven.pomderived" value="true"/>
</attributes>
</classpathentry>
<classpathentry kind="con" path="org.eclipse.m2e.MAVEN2_CLASSPATH_CONTAINER">
<attributes>
<attribute name="maven.pomderived" value="true"/>
</attributes>
</classpathentry>
<classpathentry kind="output" path="target/classes"/>
</classpath>
+23
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@@ -0,0 +1,23 @@
<?xml version="1.0" encoding="UTF-8"?>
<projectDescription>
<name>Big_Data_Assignment_2</name>
<comment></comment>
<projects>
</projects>
<buildSpec>
<buildCommand>
<name>org.eclipse.jdt.core.javabuilder</name>
<arguments>
</arguments>
</buildCommand>
<buildCommand>
<name>org.eclipse.m2e.core.maven2Builder</name>
<arguments>
</arguments>
</buildCommand>
</buildSpec>
<natures>
<nature>org.eclipse.jdt.core.javanature</nature>
<nature>org.eclipse.m2e.core.maven2Nature</nature>
</natures>
</projectDescription>
@@ -0,0 +1,2 @@
eclipse.preferences.version=1
encoding/<project>=UTF-8
+5
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@@ -0,0 +1,5 @@
eclipse.preferences.version=1
org.eclipse.jdt.core.compiler.codegen.targetPlatform=1.6
org.eclipse.jdt.core.compiler.compliance=1.6
org.eclipse.jdt.core.compiler.problem.forbiddenReference=warning
org.eclipse.jdt.core.compiler.source=1.6
+7 -5
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@@ -12,12 +12,13 @@ object KMeans {
//Create a map to store each data row with its closest cluster index as key
def train(dataset : DataFrame) : RDD[(Int,List[Float])] = {
val relevantData = dataset.select("Reputation", "CreationDate", "LastAccessDate")
val relevantData = dataset.select("Reputation")
val rows = relevantData.rdd
val rowsAsArray = rows.map(row => List(row.getInt(0).toFloat, row.getInt(1).toFloat, row.getInt(2).toFloat) )
//val rowsAsArray = rows.map(row => List(row.getInt(0).toFloat, row.getInt(1).toFloat, row.getInt(2).toFloat) )
val rowsAsArray = rows.map(row => List(row.getInt(0).toFloat) )
val K = 5 //number of intended clusters
//val n = rows.count() //number of datapoints
val m = 3 //number of features
val m = 1 //number of features
//var centres = new ArrayBuffer[Row]
//get random number generator r and use to select K centres randomly from dataset
@@ -28,7 +29,8 @@ object KMeans {
centres(a) = rows(r.ne
}*/
//val centres = rowsAsArray.takeSample(false, K, System.nanoTime().toInt)
val centres : Array[List[Float]] = Array(List(0.0f, 0.0f, 0.0f), List(10.0f, 10.0f, 10.0f), List(20.0f, 20.0f, 20.0f))
//val centres : Array[List[Float]] = Array(List(0.0f, 0.0f, 0.0f), List(10.0f, 10.0f, 10.0f), List(20.0f, 20.0f, 20.0f))
val centres : Array[List[Float]] = Array(List(0.0f), List(0.0f), List(0.0f), List(0.0f), List(0.0f))
val clusterMap :RDD[(Int,List[Float])]= rowsAsArray.map(row => (assignCluster(row,centres,m,K),row))
val newCentres = calculateNewCentres(clusterMap)
newCentres
@@ -45,7 +47,7 @@ object KMeans {
}
def assignCluster(row : List[Float], centres: Array[List[Float]], m : Int, K :Int): Int = {
var smallestNorm = 99999999999.0
var smallestNorm = 999999.0
var closestCentre = 0
for (centreNumber <- 0 until K) {
val norm = calculateNorm(row, centres(centreNumber), m)
+3 -5
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@@ -32,8 +32,10 @@ object Main {
val centresArray = centres.collect()
val unwrap = centresArray.map(x => x._2)
unwrap.foreach(println)
}
}
/*val users = dataFrames("users")
//val users = dataFrames("users")
/*val dataFrames = DataParser.ParseData()
@@ -52,7 +54,3 @@ object Main {
// Info on using DataFrames here: https://www.mapr.com/blog/using-apache-spark-dataframes-processing-tabular-data
}
}
+3 -3
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@@ -124,13 +124,13 @@ object XMLParser {
// In this case, return a placeholder value of -1.
case e: Exception => return -1
}
case DateType =>
// If the string is a date, convert from date string to long.
case DateType => return attribute
/*// If the string is a date, convert from date string to long.
var format = new java.text.SimpleDateFormat("yyyy-MM-dd'T'HH:mm:ss.SSS")
var longTime = format.parse(attribute).getTime()
// Then convert long to int representing days since epoch
var longDays : Long = longTime / (1000*60*60*24)
return longDays.toInt
return longDays.toInt*/
}
}