Tuesday, April 19, 2011

Active Learning Paper

Current version of the paper is here.

Monday, April 18, 2011

Contrast Sets

I've got which2n ported from Will1 for a baseline result. It's spitting out results like THIS.

Also, I've figured out how to embed an on_release event to the matplotlib canvas inside of my wxpython rig so that we can record clicks and display contrasts for selected regions. There will probably be 1,000,000,000 variations of the contrasts that we show (or that the user would like to see. THIS against ALL, THIS against THOSE, THIS against THAT...)

I'm having some issues with which2 and very small sections of instances so the display is waiting on that.

Planner Demo & Lua Search Algorithms

Download demo from here: https://sites.google.com/site/tanzastic/research/planner.love

Need to download LOVE from http://love2d.org, (and install; simple, takes 30 seconds) then you can just double-click to launch planner.love

- Simple demo in lua, using various search methods.
- Map and sprites based on a popular game (that I'm active with.)

Monday, April 11, 2011

Active 1NN vs. Passive&Random 1NN, CART

The plots for 24 datasets are here.

An executive summary of all these plots is here.

Tuesday, April 5, 2011

Histograms and EMD

Taken from Wikipedia, the source of all knowledge and truth:

"The earth mover's distance (EMD) is a measure of the distance between two probability distributions over a region D. Informally, if the distributions are interpreted as two different ways of piling up a certain amount of dirt over the region D, the EMD is the minimum cost of turning one pile into the other; where the cost is assumed to be amount of dirt moved times the distance by which it is moved."

Largest Earth Mover in the world -- German made. 311 feet tall, 705 feet long, 45,000 tons, can move 76, 455 cubic meters each day.

Weka style attribute Histograms (10 bins).

I can compute the EMD of two numeric columns in JM1 (5440 samples) in 0.0035 seconds.

Cliff and Application to Defect Data

Charts for TRUE (defects) class
Charts for FALSE (no defects) class

Sampling methods and Bias-Variance Trade-off

Final version of the bias-variance paper is here.