Binning data in java

Java Program to Implement Binning Method (Data Mining)

public void depth() < //depth method function
int size,bin=3,n;
System.out.println(“Enter the size of array=”);
size=sc.nextInt();
n=size/3;
System.out.println(“Enter the No’s”);
int arr[][]=new int[bin][n];
for(int j=0;j for(int i=0;i arr[j][i]=sc.nextInt();
>
>

int mean[]=new int[bin];
for(int i=0;i for(int j=0;j mean[i] += arr[i][j];
>
>
int meanarr[][]=new int[bin][n];
for(int i=0;i for(int j=0;j meanarr[i][j]=mean[i]/n;
>
>
System.out.println(“Smoothening By Mean\n”);
for(int i=0;i for(int j=0;j System.out.println(“Bin[“+i+”][“+j+”]=”+meanarr[i][j]);
>
>

public void width() int size,bin=3;
System.out.println(“Enter the size of array=”);
size=sc.nextInt();
System.out.println(“Enter the No’s”);
int arr[]=new int[size];
for(int j=0;j >

int max=arr[size-1];
int min=arr[0];
int w=(max-min)/bin;

int inter[]=new int[bin];
int inter1[]=new int[bin];
for(int i=0;i inter1[i]=min+((i+1)*w);
>

inter[0]=min;
for(int i=1;i inter[i]=inter1[i-1]+1;
>
System.out.println(“Data Entered =”);
for(int i=0;i System.out.println(arr[i]);
>

System.out.println(“Max=”+max);
System.out.println(“Min=”+min);
System.out.println(“Width=”+w);

System.out.println(“\nNumber Values in Each Bin”);
for(int i=0;i System.out.println(“Bin[“+i+”]=”+count[i]);
>

System.out.println(“Smoothening By Boundary\n”);
for(int i=0;i for(int j=0;j System.out.println(“Bin[“+i+”][“+j+”]=”+boundarr[i][j]);
>
System.out.println(“\n”);
>

public static void main(String args[]) binning b=new binning();
Scanner s = new Scanner(System.in);
System.out.println(“Press 1:Depth 2:Width 3:Exit”);
int c=s.nextInt();
if(c==1) b.depth();
>
else if(c==2) b.width();
>
else System.out.println(“Thank U”);
>
>
>

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How to generate bins for histogram using apache math 3.0 in java?

A histogram is a useful tool in data analysis to visualize the distribution of a set of numerical data. Generating bins for a histogram involves dividing the range of the data into intervals and counting the number of data points that fall into each interval. In Java, the Apache Math 3.0 library provides a convenient way to generate bins for histograms.

Method 1: Fixed Width Binning

To generate bins for a histogram using Fixed Width Binning in Apache Math 3.0, you can follow these steps:

double dataMin = 0.0; double dataMax = 100.0; double binWidth = 10.0;

FixedWidthBinning binning = new FixedWidthBinning(dataMin, dataMax, binWidth);

Histogram histogram = new Histogram(binning);

double[] data = 5.0, 10.0, 15.0, 20.0, 25.0, 30.0, 35.0, 40.0, 45.0, 50.0, 55.0, 60.0, 65.0, 70.0, 75.0, 80.0, 85.0, 90.0, 95.0>; for (double d : data)  histogram.increment(d); >

1. To retrieve the bins and bin counts, use the getBins and getCounts methods of the Histogram instance:

double[] bins = histogram.getBins(); long[] counts = histogram.getCounts();

import org.apache.commons.math3.stat.descriptive.rank.Percentile; import org.apache.commons.math3.stat.descriptive.SummaryStatistics; import org.apache.commons.math3.stat.descriptive.moment.StandardDeviation; import org.apache.commons.math3.stat.descriptive.moment.Mean; import org.apache.commons.math3.stat.descriptive.moment.Variance; import org.apache.commons.math3.stat.descriptive.SummaryStatistics; import org.apache.commons.math3.stat.Frequency; import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics; import org.apache.commons.math3.stat.descriptive.rank.Median; import org.apache.commons.math3.stat.descriptive.rank.Max; import org.apache.commons.math3.stat.descriptive.rank.Min; import org.apache.commons.math3.stat.descriptive.moment.Skewness; import org.apache.commons.math3.stat.descriptive.moment.Kurtosis; import org.apache.commons.math3.stat.descriptive.SummaryStatistics; import org.apache.commons.math3.stat.descriptive.rank.Percentile; import org.apache.commons.math3.stat.descriptive.moment.StandardDeviation; import org.apache.commons.math3.stat.descriptive.moment.Mean; import org.apache.commons.math3.stat.descriptive.moment.Variance; import org.apache.commons.math3.stat.descriptive.SummaryStatistics; import org.apache.commons.math3.stat.Frequency; import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics; import org.apache.commons.math3.stat.descriptive.rank.Median; import org.apache.commons.math3.stat.descriptive.rank.Max; import org.apache.commons.math3.stat.descriptive.rank.Min; import org.apache.commons.math3.stat.descriptive.moment.Skewness; import org.apache.commons.math3.stat.descriptive.moment.Kurtosis; import org.apache.commons.math3.stat.descriptive.SummaryStatistics; import org.apache.commons.math3.stat.descriptive.rank.Percentile; import org.apache.commons.math3.stat.descriptive.moment.StandardDeviation; import org.apache.commons.math3.stat.descriptive.moment.Mean; import org.apache.commons.math3.stat.descriptive.moment.Variance; import org.apache.commons.math3.stat.descriptive.SummaryStatistics; import org.apache.commons.math3.stat.Frequency; import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics; import org.apache.commons.math3.stat.descriptive.rank.Median; import org.apache.commons.math3.stat.descriptive.rank.Max; import org.apache.commons.math3.stat.descriptive.rank.Min; import org.apache.commons.math3.stat.descriptive.moment.Skewness; import org.apache.commons.math3.stat.descriptive.moment.Kurtosis; import org.apache.commons.math3.stat.descriptive.SummaryStatistics; import org.apache.commons.math3.stat.descriptive.rank.Percentile; import org.apache.commons.math3.stat.descriptive.moment.StandardDeviation; import org.apache.commons.math3.stat.descriptive.moment.Mean; import org.apache.commons.math3.stat.descriptive.moment.Variance; import org.apache.commons.math3.stat.descriptive.SummaryStatistics; import org.apache.commons.math3.stat.Frequency; import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics; import org.apache.commons.math3.stat.descriptive.rank.Median; import org.apache.commons.math3.stat.descriptive.rank.Max; import org.apache.commons.math3.stat.descriptive.rank.Min; import org.apache.commons.math3.stat.descriptive.moment.Skewness; import org.apache.commons.math3.stat.descriptive.moment.Kurtosis; import org.apache.commons.math3.stat.descriptive.moment.StandardDeviation; import org.apache.commons.math3.stat.descriptive.moment.Mean; import org.apache.commons.math3.stat.descriptive.moment.Variance; import org.apache.commons.math3.stat.descriptive.SummaryStatistics; import org.apache.commons.math3.stat.Frequency; import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics; import org.apache.commons.math3.stat.descriptive.rank.Median; import org.apache.commons.math3.stat.descriptive.rank.Max; import org.apache.commons.math3.stat.descriptive.rank.Min; import org.apache.commons.math3.stat.descriptive.moment.Skewness; import org.apache.commons.math3.stat.descriptive.moment.Kurtosis; import org.apache.commons.math3.stat.descriptive.moment.StandardDeviation; import org.apache.commons.math3.stat.descriptive.moment.Mean; import org.apache.commons.math3.stat.descriptive.moment.Variance; import org.apache.commons.math3.stat.descriptive.SummaryStatistics; import org.apache.commons.math3.stat.Frequency; import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics; import org.apache.commons.math3.stat.descriptive.rank.Median; import org.apache.commons.math3.stat.descriptive.rank.Max; import org.apache.commons.math3.stat.descriptive.rank.Min; import org.apache.commons.math3.stat.descriptive.moment.Skewness; import org.apache.commons.math3.stat.descriptive.moment.Kurtosis; import org.apache.commons.math3.stat.descriptive.moment.StandardDeviation; import org.apache.commons.math3.stat.descriptive.moment.Mean; import org.apache.commons.math3.stat.descriptive.moment.Variance; import org.apache.commons.math3.stat.descriptive.SummaryStatistics; import org.apache.commons.math3.stat.Frequency; import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics; import org.apache.commons.math3.stat.descriptive.rank.Median; import org.apache.commons.math3.stat.descriptive.rank.Max; import org.apache.commons.math3.stat.descriptive.rank.Min; import org.apache.commons.math3.stat.descriptive.moment.Skewness; import org.apache.commons.math3.stat.descriptive.moment.Kurtosis; import org.apache.commons.math3.stat.descriptive.moment.StandardDeviation; import org.apache.commons.math3.stat.descriptive.moment.Mean; import org.apache.commons.math3.stat.descriptive.moment.Variance; import org.apache.commons.math3.stat.descriptive.SummaryStatistics; import org.apache.commons.math3.stat.Frequency; import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics; import org.apache.commons.math3.stat.descriptive.rank.Median; import org.apache.commons.math3.stat.descriptive.rank.Max; import org.apache.commons.math3.stat.descriptive.rank.Min; import org.apache.commons.math3.stat.descriptive.moment.Skewness; import org.apache.commons.math3.stat.descriptive.moment.Kurtosis; import org.apache.commons.math3.stat.descriptive.moment.StandardDeviation; import org.apache.commons.math3.stat.descriptive.moment.Mean; import org.apache.commons.math3.stat.descriptive.moment.Variance; import org.apache.commons.math3.stat.descriptive.SummaryStatistics; import org.apache.commons.math3.stat.Frequency; import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics; import org.apache.commons.math3.stat.descriptive.rank.Median; import org.apache.commons.math3.stat.descriptive.rank.Max; import org.apache.commons.math3.stat.descriptive.rank.Min; import org.apache.commons.math3.stat.descriptive.moment.Skewness; import org.apache.commons.math3.stat.descriptive.moment.Kurtosis; import org.apache.commons.math3.stat.descriptive.moment.StandardDeviation; import org.apache.commons.math3.stat.descriptive.moment.Mean; import org.apache.commons.math3.stat.descriptive.moment.Variance; import org.apache.commons.math3.stat.descriptive.SummaryStatistics; import org.apache.commons.math3.stat.Frequency; import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics; import org.apache.commons.math3.stat.descriptive.rank.Median; import org.apache.commons.math3.stat.descriptive.rank.Max; import org.apache.commons.math3.stat.descriptive.rank.Min; import org.apache.commons.math3.stat.descriptive.moment.Skewness; import org.apache.commons.math3.stat ## Method 2: Freedman-Diaconis Binning Here is a step-by-step guide on how to generate bins for a histogram using Apache Math 3.0 in Java with Freedman-Diaconis Binning: 1. Import the necessary classes and packages: ```java import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics; import org.apache.commons.math3.stat.descriptive.rank.Percentile;

double[] data = 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0>;

DescriptiveStatistics stats = new DescriptiveStatistics(); for (double d : data)  stats.addValue(d); > double q1 = new Percentile().evaluate(data, 25); double q3 = new Percentile().evaluate(data, 75); double iqr = q3 - q1;

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Binning data in java

This class can be used to run or configure a job for performing spatial binning. Records of the input dataset will be mapped to cells (bins) of a grid.

Constructor Summary

Method Summary

Returns the current driver properties in a map where each key-value is a name and value of a command line argument.

Methods inherited from class oracle.spatial.hadoop.vector.mapred.job.IndexedInputBaseJob

Methods inherited from class oracle.spatial.hadoop.vector.mapred.job.BaseJob

Methods inherited from class java.lang.Object

Constructor Detail

Binning

Method Detail

configure

public void configure(JobConf jobConf) throws java.lang.Exception

getBinConf

getCmdOptions

public java.lang.String getCmdOptions()

getCurrentCmdArgs

public java.util.Map getCurrentCmdArgs(Configuration conf)

Returns the current driver properties in a map where each key-value is a name and value of a command line argument. By printing this information it is possible to know how to execute a similar job from command line

main

public static void main(java.lang.String[] args) throws java.lang.Exception

processArgs

public void processArgs(java.lang.String[] args, Configuration conf) throws java.lang.Exception

run

public int run(java.lang.String[] args) throws java.lang.Exception

setBinConf

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