data mining
When deploying a model, one very important thing is to monitor the results. Does it work like you’ve expected? I’m not talking about pre production […]
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analytics, data mining
Lately, I was thinking on the difference between machine learning and simulation (for prediction). Machine learning use historical inputs and outputs to find subsequent outputs. […]
data mining, relational mining
A new data mining contest is available here. The functional domain is medical, more precisely there is two tasks. First, we need to prediction if […]
data mining, text mining, web mining
Programming Collective Intelligence is a great book. It covers most of the existing data mining algorithms and presents many applications for them. It covers clustering […]
data mining, statistics
Sometimes (well most of the time) using your favorite data mining methods and the more obvious attributes are not good enough. What to do then? […]
When it comes to data mining the tool you use is very important. It seems that peoples use many software (see How many software packages […]
analytics, data mining, text mining, twitter, web mining
Now it’s time to create some clusters from our twitter data. In this post, we focus only on biographical tags and we use the old […]
data mining, text mining, twitter
After some first statistics about the twitter dataset, I try to get further. In this post, i’ve discussed how to extract token from Twitter, more […]
analytics, business, data mining
Competing on Analytics : A new Science of Winning is an interesting book even if it doesn’t explain anything about how to do real analytics. […]
Last book I read was Collective Intelligence in Action from Satman Alag (ed. Manning). It covers data mining from a web 2.0 related view. Data […]
