Boosting as a scheme for transfer learning

Here's a scenario that I believe to be common. I've got a dataset I've been collecting over time, with features \(x_1, \ldots, x_m\) This dataset will generally represent decisions I want to make at a certain time. This data is not a timeseries, it's just data I happen to have …

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Calibrating a classifier when the base rate changes

In a previous job, I built a machine learning system to detect financial fraud. Fraud was a big problem at the time - for simplicity of having nice round numbers, suppose 10% of attempted transactions were fraudulent. My machine learning system worked great - as a further set of made-up round numbers …

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Notes on setting up a Data Science app on Azure

I have recently been working on setting up a trading strategy and running it in the cloud. Although I haven't used Azure before, I wanted to try it out - some of the data science features that Microsoft advertises look pretty nice. This post is not of general interest, and most …

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Backtest your SQL queries - they are models too

I was recently discussing a project with a younger data scientist and I noticed a curious mismatch between our language. We had an API that we wanted to impose rate limits on. We want to ensure that 99% of our good customers have a good experience and never hit the …

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