# Tagged Questions

Methods and principles of selecting a subset of attributes for use in further modelling

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### Comparing and ranking differentiating attributes across groups

I'm looking for some help on how to approach this problem. Say I have two or more groups of people. Each group has characteristics and attributes. For example, say we have the following two groups: ...
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### Using non-significant variables in model

I am trying to build a credit scoring model and have discovered and interesting approach for feature selection. I am looping through all features and removing them one by one (using variable ...
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### In feature selection, are there any rules on choosing metrics to mesure relevance? (MI / Fisher score / correlation coefficient, etc)

This is a rather general question. If the question is vague and hard to answer in a few lines, I'd be happy if someone just point me to some readings. Thanks in Advance. I am working on a multi-class ...
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### Does PCA do something else apart from selecting features with the most variance?

While experimenting with Spark library MlLib, I questioned myself if I understood well the mechanism of PCA algorithm, because output of MlLib algorithm was not what I expected to get. so for given ...
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### what is “principled feature selection”?

i see the expression "principled feature selection" in titles of various Machine Learning papers and generally in the literature but nowhere do authors really define what they mean. "principled" as ...
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### How to combine a set of features and report their effectiveness with only one number?

I have a binary classification problem. My data set has 100 features with 10 different categories (10 features per category). I want to report the effectiveness (in terms of classification) with a ...
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### Random Forest: Strange Feature Importance Results for Constant Variables

I've been using the RandomForestClassifier in python's Sklearn package to assess the importance of the features in a large dataset with features that are both binary and continuous. I've done quite a ...
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### Interpreting results from lasso regression?

I have a time series data set with about 2million observations and 31 variables, which I break to a few thousand using threshold value for my dependent variable. I am using lasso regression in R to ...
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### How to determine which variables to be used for cluster analysis

I have about 10 variables (features) and want to do cluster analysis of cases (data points). I have a number of ideas about which variables to be included for cluster analysis: Plot the variables ...
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### Locality Sentive Hashing for Dimentionality Reduction or Feature clustering

So I have read up on LSH and Asymmetric hashing as proposed by Google for their google correlate algorithm. These work by only comparing similar items due to the multiple random hashes, however we are ...
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### Fixed-effects variable selection for mixed-effects regression

Does anybody know if it is possible to apply some "feature selection" algorithm to a dataset prior to creating a mixed-effects regression model? I am trying to implement such a modelling in Matlab, ...
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### taking average of several models and feature sets

just a quick question that i cant seem to find a definitive answer for. When im doing feature selection, i end up with a list of the top performing sets. Would it make sense to use the top 10 sets ...