machine learning | View Comments
previously i've discussed dimensionality reduction using SVD and PCA but another interesting technique is using a random projection.in a random projection we project A (a NxM matrix) to A' (a NxO, O < M) by the transform AP=A' where P is a MxO matrix with random values.( well not totally random, each column must have unit length (ie entries in each column must add to 1) )though the results of this reduction are generally not as good as the results from SVD or PCA it has two huge benefitscan be done without needing to hold P in memory (since it's...
books, machine learning | View Comments
for the last month or so i've had my head down and have been focusing more on theory (ie reading) than on practice (ie coding)so rather than write no blog post here's mats-list-of-cool-machine-learning-books in the order i think you should consider reading them...moreif you know nothing about machine learning and haven't done maths since high school then this is the book for you.it's a fantastically accesible introduction to the field. includes almost no theory and explains algorithms using actual python implementations.this book covers quite a bit more than programming c.i. while still being extremely practical (ie very few formula).about a...
weka, brutally short intro, machine learning | View Comments
weka is a java based machine learning workbench that i've found useful to playing with to help understand some standard machine learning algorithms. in this quick demo i show how to build a classifier for three simple datasets; two of which address the basics of text classificationbrutally short intro to weka from Mat Kelcey on Vimeo....
semi supervised, naive bayes, machine learning | View Comments
here's a great lecture from tom mitchell about document classification using a semi supervised version of naive bayes.semi supervised algorithms only require some of the training examples to be labeled and are able to make use of any unlabelled ones, very common when we have a huge corpus.i've started an experiment brewing to test this out by porting some previous naive bayes work i did to use this semi supervised scheme and will published it when it's done.cool stuff!!...
lectures, statistics, stanford, machine learning | View Comments
i'm amazed by how much great content is on youtube, how could you NOT learn something!?13 x 1hr Statistical Aspects of Data Mining (Stats 202)20 x 1hr Machine Learning...
- latent semantic analysis via the singular value decomposition (for dummies)
- semi supervised naive bayes
- statistical synonyms
- round the world tweets
- decomposing social graphs on twitter
- do it yourself statistically improbable phrases
- should i burn it?
- the median of a trillion numbers
- deduping with resemblance metrics
- simple supervised learning / should i read it?
- audioscrobbler experiments
- chaoscope experiment