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deep learning

2

Answers

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    [Deleted User][Deleted User] Posts: 0 Learner III
    varunm1 
    you are perfect teacher o:)
    I will try all the points that you mentioned :)
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    [Deleted User][Deleted User] Posts: 0 Learner III
    edited April 2019
    @varunm1  @sgenzer
    it works but cross validation doesnt show accuracy or kappa :'(:'(
    please help me to solve it
    thank you o:)
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    [Deleted User][Deleted User] Posts: 0 Learner III
    look at the process please :(
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    [Deleted User][Deleted User] Posts: 0 Learner III
    edited April 2019
    @varunm1
    About "getting a label with a single sample" is possible in predicting of cancer because cancer cell is unique between cells
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    [Deleted User][Deleted User] Posts: 0 Learner III
    edited April 2019
    @varunm1  @sgenzer mschmitz
    please look at the screenshot it doesnt calculate kappa or accuracy.
    please help me to solve that
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    [Deleted User][Deleted User] Posts: 0 Learner III
    varunm1   Hi
    I will try it now
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    [Deleted User][Deleted User] Posts: 0 Learner III
    varunm1 
    yes it works <3o:) thank you <3
    I did all the points that you told me about data 
     but the result is fun ;) some of the algorithm results changed to better some of the is not. Logically the result is fun :D
    any way thank you very much my kind friend o:)
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    [Deleted User][Deleted User] Posts: 0 Learner III
    varunm1 
    I agree with you. but i remove all the single labeled data.
    Thank you <3 
    Regards
    mbs
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    [Deleted User][Deleted User] Posts: 0 Learner III
    varunm1 
    where can I read about cross validation?

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    [Deleted User][Deleted User] Posts: 0 Learner III
    sgenzer
    Hi
    thank you for your link but sorry it is too fast :(
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    varunm1varunm1 Moderator, Member Posts: 1,207 Unicorn
    Search for answers in this community or academy. Finally, Google is your best friend. Try searching until you find something you can understand because we cannot know which is the best one for you. Read different things, and you will get to know easily. As our time is limited, we recommend you try hard first and then ask us questions in case you have any. This the way we learn as well.
    Regards,
    Varun
    https://www.varunmandalapu.com/

    Be Safe. Follow precautions and Maintain Social Distancing

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    [Deleted User][Deleted User] Posts: 0 Learner III
    @varunm1
    according to this link:
    https://community.rapidminer.com/discussion/55112/cross-validation-and-its-outputs-in-rm-studio
    because of the 2000 number of excel that I have ( large data) split data work better than cross validation.
    During the test I understand that if I combine 3 or 4 algorithm and use cross validation the result is better than split data.
    Regards
    mbs
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    [Deleted User][Deleted User] Posts: 0 Learner III
    @varunm1
    Thank you for all the points that you mentioned.
    With your perfect suggestion my thesis doesnt have any problem and I'm sure that I will pass it easily.
    Regards
    mbs

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    [Deleted User][Deleted User] Posts: 0 Learner III
    your article in 4th of March about cross validation was perfect ;):)
     

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    [Deleted User][Deleted User] Posts: 0 Learner III
    For reason 2, you need to start from smaller networks and then build more complex networks based on data and test performance. There is no use of building networks with more hidden layers when a simple neural network can achieve your task.
    For reason 3, use AUC  values as performance metric instead of accuracy.
    Reason 2: The complex algorithms overfit some times (depends on data). A deep learning algorithm is the one which has more hidden layers. In my statement, I am saying to train and test a model with a single hidden layer first and then note the performance parameters like accuracy, kappa, etc. Then you can build another model with more hidden layers and see the performances. If your simple model is giving the best performance there is no need to use a complex model with multiple hidden layers.
    @varunm1
    These are your suggestion but I couldnt understand them and they are important. so please make an example with them and share your xml.
    Thank you very much
    mbs
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    [Deleted User][Deleted User] Posts: 0 Learner III
    thank you again <3
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    [Deleted User][Deleted User] Posts: 0 Learner III
    edited May 2019
    Hi
    @varunm1
     According to your previous help please tell me how can I use more than 1 algorithm and combine them then use cross validation without using group model?
    According to the points that @varunm1 said if we have a data with label we dont need to  separate dataset in to traning and testing. And also RM with cross validation is able to separte it automatically to the train and test parts And for the testing part it will not use the label like the training part. 
    Are these points correct?
    Thank you
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    [Deleted User][Deleted User] Posts: 0 Learner III
    edited May 2019
    @varunm1

    Thank you for your great answer again. <3
    the algorithms are:
    1. deep learning
    2. j48
    3. random forest
    4. knn
    5. gradient boosted tree
    6. neural network
    7. svm
    Thank you for the time that you spend on my questions o:)

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    varunm1varunm1 Moderator, Member Posts: 1,207 Unicorn
    @mbs

    Are you trying to combine all these models into a single model?  (or) are you trying to get cross-validation performance of each model separately?

    I never tried combining these many models into a single model. You can try using group models but not sure how it works.
    Regards,
    Varun
    https://www.varunmandalapu.com/

    Be Safe. Follow precautions and Maintain Social Distancing

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    [Deleted User][Deleted User] Posts: 0 Learner III
    edited May 2019
    @varunm1

     the result of them are perfect.The accuracy of them is around 99.5. this is "Ensemble learning".
    Ensemble methods are meta-algorithms that combine several machine learning techniques into one predictive model in order to decrease variance (bagging), bias (boosting), or improve predictions (stacking).
    look at this link please.
    https://en.wikipedia.org/wiki/Ensemble_learning

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    [Deleted User][Deleted User] Posts: 0 Learner III
    edited May 2019
    >Do you mean that I have to separate dataset in to traning and testing?
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    [Deleted User][Deleted User] Posts: 0 Learner III
    edited May 2019
    @varunm1

    please explain more. ;)
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