Thanks everyone for the suggestions. Actually we thought of gathering more data but the point is we do not have many speed bumps in our driving area. If we drive over the same speed bump again and again it may not add anything really novel to the data.
I think a combination of oversampling and sample_weight along with ROC may be a good start for me. Thanks, Amita On Fri, Aug 5, 2016 at 11:55 AM, Jared Gabor <jgabor.as...@gmail.com> wrote: > Lots of great suggestions on how to model your problem. But this might be > the kind of problem where you seriously ask how hard it would be to gather > more data. > > On Thu, Aug 4, 2016 at 2:17 PM, Amita Misra <amis...@ucsc.edu> wrote: > >> Hi, >> >> I am currently exploring the problem of speed bump detection using >> accelerometer time series data. >> I have extracted some features based on mean, std deviation etc within a >> time window. >> >> Since the dataset is highly skewed ( I have just 5 positive samples for >> every > 300 samples) >> I was looking into >> >> One ClassSVM >> covariance.EllipticEnvelope >> sklearn.ensemble.IsolationForest >> >> but I am not sure how to use them. >> >> What I get from docs >> separate the positive examples and train using only negative examples >> >> clf.fit(X_train) >> >> and then >> predict the positive examples using >> clf.predict(X_test) >> >> >> I am not sure what is then the role of positive examples in my training >> dataset or how can I use them to improve my classifier so that I can >> predict better on new samples. >> >> >> Can we do something like Cross validation to learn the parameters as in >> normal binary SVM classification >> >> Thanks,? >> Amita >> >> Amita Misra >> Graduate Student Researcher >> Natural Language and Dialogue Systems Lab >> Baskin School of Engineering >> University of California Santa Cruz >> >> >> >> >> >> -- >> Amita Misra >> Graduate Student Researcher >> Natural Language and Dialogue Systems Lab >> Baskin School of Engineering >> University of California Santa Cruz >> >> >> _______________________________________________ >> scikit-learn mailing list >> scikit-learn@python.org >> https://mail.python.org/mailman/listinfo/scikit-learn >> >> > > _______________________________________________ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn > > -- Amita Misra Graduate Student Researcher Natural Language and Dialogue Systems Lab Baskin School of Engineering University of California Santa Cruz
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