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Jul
1
awarded  Nice Question
Jun
26
revised How to Filter Junk Features Automatically
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Jun
26
answered How to Filter Junk Features Automatically
Jun
24
awarded  Notable Question
Jun
19
comment Books for self-studying time series analysis?
@IrishStat Every dataset in FPP is non-simulated. Seems like great data to learn on...
Jun
18
comment Books for self-studying time series analysis?
@TomReilly Whatever the issues with any particular model, I'd still recommend the R language in general and the forecast package in particular to anyone looking to learn time series analysis. You really can't beat free, especially if your goal is education.
Jun
17
answered Books for self-studying time series analysis?
Jun
8
comment How to do Principal Components Analysis from start to finish in Python or R?
@EdwardJ.Stembler Ahah! You've got a really good question buried in this post. PCA is pretty easy when all your data are already numeric... it's a lot harder when you have a mix of categorical and numeric data (and EVEN harder if some of your data have missing values). If you can identify the core of your issue and re-post an example dataset you're having trouble with, someone on this site can probably help you.
Jun
8
revised How to do Principal Components Analysis from start to finish in Python or R?
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Jun
8
revised How to do Principal Components Analysis from start to finish in Python or R?
added 256 characters in body
Jun
8
comment How to do Principal Components Analysis from start to finish in Python or R?
@EdwardJ.Stembler A good PCA routine will center and scale the data for you.
Jun
8
revised How to do Principal Components Analysis from start to finish in Python or R?
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Jun
8
revised How to do Principal Components Analysis from start to finish in Python or R?
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Jun
8
answered How to do Principal Components Analysis from start to finish in Python or R?
Jun
4
revised Random forests vs boosting
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Jun
4
comment Estimating the best length of n-gram
What are you going to do with these n-grams? If you're just going to look at them, the best number is whichever looks prettiest =D. If you're building some kind of model the best number of n-grams is whatever gives your model the best performance on an out-of-sample dataset.
May
13
awarded  Enlightened
May
13
awarded  Nice Answer
May
2
comment Are models identified by auto.arima() parsimonious?
@forecaster You should accept one of the answers to this question.
Apr
9
awarded  Popular Question