Hacking Cough - Chris Edwards' blog: Scientific method's deat...
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Saved by 1 people (0 private), first by anonymouse user on 2008-07-01
- Imrchen on 2008-07-01 - Tags data mining , google , thinking
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But the core of all that Google does right now is based on a statistical approach that makes some basic assumptions about how language works. You might call it a model.
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Yet, machine-learning algorithms depend on the construction of some kind of model. It is not necessarily a deterministic model in the way that classical mechanics is, but just because it invokes statistics does not make it any less a model-based technique.
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Professor Jaroslav Stark of Imperial College sees modelling as a key to understanding what goes on inside living systems precisely because models are often inaccurate. For him, the fact that a model diverges from reality provides important clues to interactions that need to be taken into account. And they can provide a way to probe interactions where it is simply not possible to use traditional methods such as turning genes off selectively because that introduces other interactions
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But that is what science is like: it finds new information, assimilates it and moves on.
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Big computers can certainly help with the creation and execution of models. But it seems unlikely that unleashing petaflops and petaflops on a problem blind is going to do much for machine learning.
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Kelly discounts idea of the approach killing scientific method. But dreams up a new term for it: "correlative analytics".
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the people doing real work on this stuff will be asking themselves: how was the data collected; what were the conditions? In short, while they may not read the data, they will attempt to understand how it came into being and then try to fit it into a model.
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The original use of the term data mining was pejorative: if you have enough data and search long enough, you can always find some model that fits your data arbitrarily well.
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Say what you will about the quality of our available scientific models, but the scientific method of hypothesis testing is here to stay.
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