Notes on codes, projects and everything
Machine Learning
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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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Further Hack on the Multi-Dimensional Approximate Neighbour Search
Traversing a tree structure often involves writing a recursive function. However, Python isn’t the best language for this purpose. Therefore I started flattening the tree into a key-value dictonary structure. Logically it is still a tree, but it is physically stored as a dictionary. Therefore it is now easier to write a simple loop to traverse it.
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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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Random notes on Pandas and Scikit-learn
So I first heard about Panda probably a year ago when I was in my previous job. It looked nice, but I didn’t really get the chance to use it. So practically it is a library that makes data looks like a mix of relational database table and excel sheet. It is easy to do query with it, and provides a way to process it fast if you know how to do it properly (no, I don’t, so I cheated).
Random Posts
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Oh NO! My print output is chopped!
So my cheat with dask worked fine and dandy, until I started inspecting the output (which was to be used as an input for another script). While the script seemed to work fine, however when I started to parse each line I was hit with some funny syntax errors. After some quick inspection I found some of the lines was not printed completely.
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Development virtual machines on OS X using VirtualBox and Ubuntu
I have been following this excellent guide written by Benjamin Thomas to set up my virtual machine for development purpose. However, when I am starting to configure a Ubuntu Quantal alpha machine, parts of the guide became inapplicable. Hence, this post is written as a small revision to the previously mentioned guide.
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Working Environment Setup, for 2020
In recent years, I start to make my development environment decouple from the tools delivered by the package manager used by the operating system. The tools (compiler, interpreters, libraries etc) are usually best left unmodified so other system packages that rely on them keeps working as intended. Also another reason for the setup is I wanted to follow the latest release as much as possible, which cannot be done unless I enroll myself to a rolling release distro.
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Semantic Web
I am currently preparing myself in applying a postgrad programme and is looking for a research topic. At first I wanted to do something that is related to cloud computing but after some discussion with people around me, they suggest me to do something on semantic web. While posting my notes here, I realized that I had posted something on semantic network that looks like the base of semantic web here (Post still “Under construction” as of writing, will post the diagrams later tonight).
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Adding complexity to the bot: threads and processes
Being new to asyncio, after publishing the previous post on running multiple applications in one event loop, I also cross posted it to the discussion board for feedback. So apparently instead of cramming everything to the same event loop, it would be better if each application run on a separate thread. That makes sense, considering all the code that was written for that.
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