I am relatively new to machine learning and have recently had some exposure to Decision Trees, Boosting, Bagging, and Random Forests. This has created an interest for me in this field and am now considering writing my thesis incorporating some of these algorithms. I have several ideas in mind, however the data I am currently looking to use is that of the time-series variety. My question is this, is it possible within the current framework of these machine learning algorithms to use time-series, and if so, what are some of the pitfalls I should be watching out for as they apply to both time-series and machine learning. If it matters I will be using Python for this, if any one wants to chime in with direct references to coding. Thanks!
closed as too broad by usεr11852, mdewey, John, Matthew Drury, whuber♦ Dec 30 '16 at 1:37
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