annoy

• Regression with 2-means clustering Annoy (non-scientific)

  So apparently Annoy is now splitting points by using the centroids of 2 means clustering. It is claimed that it provides better results for ANN search, however, how does this impact regression? Purely out of curiosity, I plugged a new point splitting function and generated a new set of points.

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• Regression with Annoy (cont’d)

  After a year and half, a lot of things changed, and annoy also changed the splitting strategy too. However, I always wanted to do a proper follow up to the original post, where I compared boosting to Annoy. I still remember the reason I started that (flawed) experiment was because I found boosting easy.

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• Quick experiment, boosting vs annoy

  While following through the Statistical Learning course, I came across this part on doing regression with boosting. Then reading through the material, and going through it makes me wonder, the same method may be adapted to Erik Bernhardsson‘s annoy algorithm.

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• Approximate Neighbour Search in Multiple Dimensions

  In the previous post, I re-implemented Annoy in 2D with some linear algebra maths. Then I spent some time going through some tutorial on vectors, and expanded the script to handle data in 3D and more. So instead of finding gradient, the perpendicular line in the middle of two points, I construct a plane, and find the distance between it and points to construct the tree.

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• Re-implementing Approximate Nearest Neighbour Search

  Recently I switched my search code to Annoy because the input dataset is huge (7.5mil records with 20k dictionary count). It wasn’t without issues though, however I would probably talk about it next time. In order to figure out what each parameters meant, I spent some time watching through the talk given by the author @fulhack.

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• Information Retrieving with ….. a lot of libraries

  Implementing a Information Retrieval system is a fun thing to do. However, doing it efficiently is not (at least to me). So my first few attempts didn’t really end well (mostly uses just Go/golang with some bash tricks here and there, with or without a database). Then I jumped back to Python, which I am more familiar with and was very surprised with all the options available. So I started with Pandas and Scikit-learn combo.

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Random Posts

• Hello World from Zend MVC

  This post continued from this post. Finally I have found some time to start developing my pet project using Zend Framework. After getting the controller to work the way I am more familiar (comparing to Kohana which I used at work) with, the next step is to get it to output some data.

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• My evil evil form and database library

  Writing a usable form and database library has always been a painful experience. So why bother re-inventing the wheel when there are so many to choose from already? I am writing one mostly for learning purpose. After numerous attempts, I finally get my form and database library in shape. It is nowhere complete, but nor it is perfect, but it is currently the implementation that is closest to my original design. I will keep working on it so it can be used in my personal projects in the future.

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• Generating grids in javascript

  Recently I find some of my pet projects share a common pattern, they all are based on some kind of grids. So I find myself writing similar piece of code over and over again. While re-inventing wheels is quite fun, especially when you learn new way of getting things done with every iteration, it is actually quite tedious after a while.

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• Slideshow using Scriptaculous

  I need a slide show script for my portfolio pages but couldn’t find a good one anywhere so I decided to write one myself. The slide show script will be able to display image and the respective description in a predefined order. However, in this version, visitors would not be able to directly jump to a particular slide yet. The script is written in prototype‘s object-orientation approach hence you need to have prototype called.

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• Dragon Curve

  I really don’t know how to start explaining what is a Dragon Curve. However, I find it is interesting enough after finding out that there’s actually a fixed pattern of occurrence. Therefore I spent some time writing a series of scripts to plot the generated fractal into a graph. What I didn’t expect is, the series get really complicated after a while.

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