I was inspired to write this post after I read Foquant’s (formerly CPP Trader) post on Inductive versus Deductive Algorithms. He hits the nail on the head when he ends his article with:
Personally, I have used deductive reasoning to develop frameworks for money management methods, and then tested data in a similar, inductive method, [...]

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Yes you read that right, I’m working on a new set of RapidMiner tutorial posts (I’m bagging the videos for now). I hope to share with my readers two new tutorials over the coming weeks/months and I expect to post the first installment this week.
The first tutorial will be about using RapidMiner’s Evolutionary [...]

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I was inspired to write a short post about trimming outliers in RapidMiner after a comment from dc yesterday. Although I’ve never used these particular set of data pre-processing operators (I always inspect my data visually), I find them to interesting and worth a look.
If you right click and select “New Operator”, you’ll find [...]

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I mentioned in my supervised learning post that your data model will only be as good as your training data. Too often, and I’ve been guilty of this as well, data modelers throw all kinds of inputs variables together into a training data set figuring the neural net learner needs them all. They [...]

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I created a chart of the S&P500 daily % changes, squared them, and put them into an Excel chart. An interesting perspective was charted relative to the daily volatility and its spikes over the past 14 years. Most notable is that little spike we had on February 27, 2007. Something tells [...]

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