[mlpack-git] (blog) master: blog post week 5. (a12a45d)

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Repository : https://github.com/mlpack/blog
On branch  : master
Link       : https://github.com/mlpack/blog/compare/7702acd3b5039103ea326b726ba9f16a91a4f2df...a12a45d2e7bf89a3a935d5462c8f9198bc13fadc

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commit a12a45d2e7bf89a3a935d5462c8f9198bc13fadc
Author: MarcosPividori <marcos.pividori at gmail.com>
Date:   Mon Jun 27 17:34:07 2016 -0300

    blog post week 5.


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+Title: Approximate Nearest Neighbor Search - Week 5
+Date: 2016-06-27 21:00:00
+Tags: gsoc, knn, kfn
+Author: Marcos Pividori
+
+Last week, I have been working on the benchmarking system [[1]](https://github.com/zoq/benchmarks/pull/17).
+After considering different options, I created a new view to plot the progress of a specific metric for different values of a method parameter. For example, for knn, it is possible to analyze the number of base cases and runtime for different values of approximation error (epsilon), with different libraries/configurations.
+
+I executed some tests for: mlpack_knn with cover trees and kdtrees, and other libraries like [ANN](https://www.cs.umd.edu/~mount/ANN/) and
+[FLANN](http://www.cs.ubc.ca/research/flann/). Results are available on: [[2]](http://marcospividori.github.io/mlpack-app/) ("Metric analysis with multiple parameters for an algorithm/dataset combination.")
+
+We plan to benchmark approximate neighbor search with bigger datasets, using Jenkins's servers.
+
+Next week, I will continue working in the implementation of Spill Trees [[3]](http://machinelearning.wustl.edu/mlpapers/paper_files/NIPS2005_187.pdf). I will consider different approaches to include this extension and analyse the possibility of implementing Hybrid SP-Tree Search as a dual tree algorithm.