Implement a Kmeans algorithm using MapReduce to cluster the provided data set.

A 2-d data with 100,000 instances

is provided. You can code it with any programming language you prefer.

Basic Tasks:

1. Describe how you implement the K-means using Mapreduce and what problems you’ve


2. Run the algorithm in a single iteration with different number of k: k =60, k= 80 and k=100.

3. Report the execution time with different k in a single iteration: k =60, k= 80 and k=100.

4. Submit your Java file/ other format of programming file with comments and detail documentation

on how to execute your code (or a Readme file).

Figure out a way that you can run the algorithm with 30 iterations with a k= 100. Report

your results (the final centers and the assignments for each centers).

After you’ve finished the first question, visualize your result using a 2-d plot.

Testing to be done using hadoop

NOTE: the deadline for this project is tuesday 11/25/18 EST 10:00 am

Квалификация: Алгоритмы, Hadoop, Java, Map Reduce

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ID проекта: #18231770



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