Cross-validation in MatLab

Cross-validation is a technique that help one to estimate the error precisely in terms of statistics. Two common types:

– leave-one-out cross validation: use only observation for testing, and the other for training –> use in data set with sparse data.

– k-fold cross validation (we often use k = 10): divide the dataset into k parts equally, then iteratively use one part for testing and the other parts for training. Finally, compute the average error.

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26 Responses to “Cross-validation in MatLab”

  1. Ron Says:

    You might wanna check an open source k-fold cross validation tool:
    http://www.cs.technion.ac.il/~ronbeg/gcv/

  2. aryu Says:

    do you have a documentation to implement 10 cross validation in matlab? please send me an email.. thx

  3. srividya Says:

    sir i need k-fold cross validation code using matlab it may be 4 or 5 fold cross validation plz help me any one

  4. ziba Says:

    hi i also need k-fold cross validation code using matlab. plz help me.it is ergent

  5. Lakshmen Says:

    I also would like to have a copy of the code. Can u send it to my email

  6. kritika Says:

    I also want a code for 3-fold cross validation. If you get the code then please sent it to me also.

  7. itsme Says:

    how to perform m-fold cross validation for neural classifier?? please help ??

  8. jenifer Says:

    pls anyone send me the matlab codes for 3 fold cross validation for svm classifier.. pls help me friends

  9. Jessica Says:

    can someone help me with 5 fold cross validation?

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