mbq

Warsaw, Poland

mbq.me

Age: 28

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awarded Nice Question
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revised Estimating parameters of Dirichlet distribution
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asked Substantial overlap with Computational Science
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comment Support Vector Machines and the curse of dimensionality
Well, obviously with a finite sample you can never be sure that some association is not spurious, but IMHO the fact that a feature keeps appearing in such a procedure is pretty much the best confirmation you can get. And still there is an issue whether something is missing (; You can also check out my paper where something like this is used to benchmark few RF-based feature selectors.
Feb
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comment Support Vector Machines and the curse of dimensionality
Sure. Still this "stochastic agreement" may also fail; if only spurious features are selected, they will be likely different each time and there will be no consensus. This is why FS should be all relevant as defined in this Nilsson et al paper.
Feb
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answered Support Vector Machines and the curse of dimensionality
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revised Does the number of rows really matter beyond a point?
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awarded Nice Answer
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awarded Good Question
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revised Selecting knots for a GAM
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revised Why is there no intercept in a regression model equation with standardized coefficients?
Formatting fixes.
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answered What is the difference between feature selection and dimensionality reduction?
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revised What is your favorite "data analysis" cartoon?
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comment Is it better to use MAE or MSE for perfomance measure?
The point is that you make such plots for RF and SVM, go to your forest people and discuss which distribution of error suits them better. This way you will do a rational choice between methods, not some random-people-on-the-internet-told-me-that-one-number-is-more-magic-than-other thing.
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