https://www.cs.berkeley.edu/~jordan/courses/294-fall09/lectures/feature/slides.pdf http://www.cs.princeton.edu/courses/archive/spring10/cos424/slides/18-feat.pdf http://www.cs.princeton.edu/courses/archive/spring10/cos424/w/rinfo https://www.kaggle.com/c/springleaf-marketing-response/forums/t/16676/good-examples-of-feature-engineering http://www.cs.stanford.edu/people/chrismre/papers/mythical_man.pdf http://datascience.stackexchange.com/questions/8286/are-there-any-tools-for-feature-engineering http://pslcdatashop.org/KDDCup/workshop/papers/kdd2010ntu.pdf http://dspace.mit.edu/handle/1721.1/90409 http://homes.cs.washington.edu/~pedrod/ https://homes.cs.washington.edu/~pedrod/papers/cacm12.pdf At the end of the day, some machine learning projects succeed
and some fail. What makes the difference? Easily
the most important factor is the features used. If you have
many independent features that each correlate well with the
class, learning is easy. On the other hand, if the class is
a very complex function of the features, you may not be
able to learn it. 1 Answer Sean Gerrish, PhD in ML, Tech lead of stats-y machine-learning-y groups at Google Sometimes people using a machine learning algorithm implement it themselves. This is a project that might take an hour or a week of someone's time (or more, depending on the algorithm and the skill of the person implementing it). An "off the shelf" algorithm is one that has been implemented by someone else and is available in a library. Usually this means it has been so in a fairly generic way, and usually there will be some room for improvement (e.g., by selecting or transforming features). @article{Domingos:2012:FUT:2347736.2347755, author = {Domingos, Pedro}, title = {A Few Useful Things to Know About Machine Learning}, journal = {Commun. ACM}, issue_date = {October 2012}, volume = {55}, number = {10}, month = oct, year = {2012}, issn = {0001-0782}, pages = {78--87}, numpages = {10}, url = {http://doi.acm.org/10.1145/2347736.2347755}, doi = {10.1145/2347736.2347755}, acmid = {2347755}, publisher = {ACM}, address = {New York, NY, USA}, } |
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