Notes on codes, projects and everything
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.
(more…)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.
(more…)This post is purely based on my own speculation as there’s no experiment on real-life data to actually back the arguments. I am currently trying to document down a plan for my experiment(s) on recommender system (this reminds me that I have not release the Flickr data collection tool :/) and my supervisor advised to write a paragraph or two on some of the key things. Since he is not going to read it, so I might as well just post it here as a note.
I was asked to evaluate fuzzy c-means to find out whether it is a good clustering algorithm for my MPhil project. So I spent the whole afternoon reading through some tutorial to get some basic understanding. Then I thought why not implement it in Clojure because it doesn’t look too complicated (I was so wrong…).
While the previous file structure works well, I decided to tune some details before deploying the latest WordPress release. Besides that, I also started a new theme development project after my last theme which was developed more than 2 years ago. Thankfully, everything seems to work so far.
Back then when I was attending a job interview, I was asked to write a Fizz Buzz program to prove that my coding ability. There was only a pen and a piece of paper, so basically means there’s no way I can refer to the documentation for the API syntax. Fortunately I somehow managed to remember and not screw up.
Just happened to see this post a few months ago, and the author created another cloud that uses almost the same technique to ‘visualize’ a list of countries. The author uses PHP to generate the cloud originally and I thought I may be able to do in javascript. After some quick coding I managed to produce something similar to the first example, source code after the jump.
This is the second part of the golang learning rant log. Previously on (note (code cslai)) I managed to make each line in the CSV into a hash map. So today I am going to make it into JSON Lines.
After reading through the documentation, I find that the role based ACL and work flow can be more tightly integrated. Therefore I made all the transaction into many FSMs and my work flow component now consists of one work flow library and one work flow management model. As I am going a more normalized design (I use denormalized design in work as it deals with a lot of documents, however for a small project like mine, a denormalized design should do well).