ML algorithms work with numerical data but in your scenario response variable is represented as strings. Encode strings with numerical values. If you carefully read the error message you will be able to understand the root course of the error.
Additionally, nowadays Iris is considered as a toy dataset and not suitable for training big deep networks. Please, use one of the datasets mentioned in my previous email. On Thu, May 12, 2016 at 11:37 PM, Lakini Senanayaka < lakinisenanayak...@gmail.com> wrote: > Hi, > > I have gone through DL4J examples which are given in DL4J documentation > [1] > I have studied convolution nets,feed forward nets-classification,and > Restricted Boltzmann machines. > > I have tried to implement my own model using linear classification feed > forward network as in the example [2].You can find my git repo here[3] > In here I used Iris Data set[4] and I have encountered a problem while > running the code. > > This is my error log. > > INFO: successfully loaded > C:\Users\Lakini\AppData\Local\Temp\jniloader9080956326584987445netlib-native_system-win-x86_64.dll > Exception in thread "main" java.lang.NumberFormatException: For input > string: "Iris-setosa" > at > java.lang.NumberFormatException.forInputString(NumberFormatException.java:65) > at java.lang.Integer.parseInt(Integer.java:580) > at java.lang.Integer.parseInt(Integer.java:615) > at org.canova.api.io.data.Text.toInt(Text.java:615) > at > org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator.getDataSet(RecordReaderDataSetIterator.java:204) > at > org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator.next(RecordReaderDataSetIterator.java:150) > at > org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator.next(RecordReaderDataSetIterator.java:288) > at > org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator.next(RecordReaderDataSetIterator.java:42) > at > org.deeplearning4j.nn.multilayer.MultiLayerNetwork.fit(MultiLayerNetwork.java:1149) > at > org.deeplearning4j.examples.feedforward.classification.MLPClassifierLinearIrisData.main(MLPClassifierLinearIrisData.java:85) > at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) > at > sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) > at > sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) > at java.lang.reflect.Method.invoke(Method.java:497) > at com.intellij.rt.execution.application.AppMain.main(AppMain.java:144) > > As I understood the error is occurring because I didn't vectorise the data > set in to a numerical form. > > Is there any method to vectorise CSV using canova using DL4J libraries, > without installing and using Canova Cli separately? > > > [1]DL4J Documentation <http://deeplearning4j.org/> > [2]MLPClassifierLinear > <https://github.com/deeplearning4j/dl4j-0.4-examples/blob/master/src/main/java/org/deeplearning4j/examples/feedforward/classification/MLPClassifierLinear.java> > [3]MLPClassifierLinearIrisDataSet > <https://github.com/Lakini/dl4j-0.4-examples/blob/master/src/main/java/org/deeplearning4j/examples/feedforward/classification/MLPClassifierLinearIrisDataSet.java> > [4]Iris Dataset > <https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data> > > On Sat, May 7, 2016 at 6:42 PM, Lakini Senanayaka < > lakinisenanayak...@gmail.com> wrote: > >> Thank you Upul. I will do that. >> >> Thank you, >> Lakini Senanayaka >> >> On Sat, May 7, 2016 at 10:10 AM, Upul Bandara <u...@wso2.com> wrote: >> >>> +1 for maintaining a blog. >>> >>> Regarding DL4J, no need to go very deep. Please familiar with its API >>> and you should be able to build common NN architectures such as fully >>> connected networks, convolution networks and recurrent networks using DL4J. >>> >>> So try to build few models using publically available datasets such as >>> MNIST, CIFAR-10. >>> >>> Regarding front-end development: Please do some research and find out >>> few libraries that we can use for building our drag & drop UI. >>> >>> Thanks, >>> Upul >>> >>> On Fri, May 6, 2016 at 10:14 PM, Lakini Senanayaka < >>> lakinisenanayak...@gmail.com> wrote: >>> >>>> Hi all, >>>> >>>> I have gone through the Machine Learner source code[1][2].I am still >>>> reading DL4J and ND4J documentations.Do I need to understand and study the >>>> DL4J in deep? >>>> Do I need to maintain a blog about my GSoC project? >>>> >>>> Could you please give me further guidance and the next steps to follow? >>>> >>>> [1] https://github.com/wso2/carbon-ml >>>> [2] https://github.com/wso2/product-ml >>>> >>>> Thank you. >>>> Lakini Senanayaka. >>>> >>>> On Tue, May 3, 2016 at 2:30 PM, Lakini Senanayaka < >>>> lakinisenanayak...@gmail.com> wrote: >>>> >>>>> Hi all, >>>>> >>>>> Thank you very much.I will go through these links. >>>>> >>>>> On Tue, May 3, 2016 at 2:00 PM, Lakini Senanayaka < >>>>> lakinisenanayak...@gmail.com> wrote: >>>>> >>>>>> Hi, >>>>>> >>>>>> Thank you for the response Supun.I thought I am out from the >>>>>> competition as no one replied me at least for my first mail. >>>>>> Thank you so much. >>>>>> >>>>>> On Tue, May 3, 2016 at 9:43 AM, Supun Sethunga <sup...@wso2.com> >>>>>> wrote: >>>>>> >>>>>>> Hi Lakini, >>>>>>> >>>>>>> Sorry for the delay in getting back to you. While you are reading >>>>>>> about DL4J, you can setup your dev environment and get familiarized with >>>>>>> the Machine Learner source code. For that, you can fork the following >>>>>>> two >>>>>>> repos [1] [2] and try to build from the source (when you do some code >>>>>>> change to [1], you have to build the two repos in order). >>>>>>> Implementations >>>>>>> of the existing algorithms can be found at [3]. You can refer those to >>>>>>> get >>>>>>> an idea on the code conventions and the implementation patterns used. >>>>>>> Please feel free o ask if you have any questions. >>>>>>> >>>>>>> Meantime, Upul will give you the steps on how to proceed with the >>>>>>> project. >>>>>>> >>>>>>> [1] https://github.com/wso2/carbon-ml >>>>>>> [2] https://github.com/wso2/product-ml >>>>>>> [3] >>>>>>> https://github.com/wso2/carbon-ml/tree/master/components/ml/org.wso2.carbon.ml.core/src/main/java/org/wso2/carbon/ml/core/spark/algorithms >>>>>>> >>>>>>> Regards, >>>>>>> Supun >>>>>>> >>>>>>> On Mon, May 2, 2016 at 8:26 AM, Lakini Senanayaka < >>>>>>> lakinisenanayak...@gmail.com> wrote: >>>>>>> >>>>>>>> Hi, >>>>>>>> >>>>>>>> Thank you very much for accepting my project proposal and all the >>>>>>>> comments,feedback and help, you did to prepare a good proposal. >>>>>>>> >>>>>>>> I have started the project as in my project time line. >>>>>>>> These days I am reading DL4J concepts and it's documentation and >>>>>>>> started to learn Jaggery as it will be useful in front end >>>>>>>> development.As >>>>>>>> well as I have started learning REST APIs. >>>>>>>> >>>>>>>> I like to know WSO2 coding conventions and other information >>>>>>>> related to my project.I'm looking forward for further guidance. >>>>>>>> >>>>>>>> >>>>>>>> -- >>>>>>>> Thank you. >>>>>>>> >>>>>>>> Sincerely, >>>>>>>> *Lakini Senanayaka.* >>>>>>>> >>>>>>>> >>>>>>>> _______________________________________________ >>>>>>>> Dev mailing list >>>>>>>> Dev@wso2.org >>>>>>>> http://wso2.org/cgi-bin/mailman/listinfo/dev >>>>>>>> >>>>>>>> >>>>>>> >>>>>>> >>>>>>> -- >>>>>>> *Supun Sethunga* >>>>>>> Software Engineer >>>>>>> WSO2, Inc. >>>>>>> http://wso2.com/ >>>>>>> lean | enterprise | middleware >>>>>>> Mobile : +94 716546324 >>>>>>> >>>>>> >>>>>> >>>>>> >>>>>> -- >>>>>> Thank you. >>>>>> >>>>>> Sincerely, >>>>>> *Lakini Senanayaka.* >>>>>> >>>>>> >>>>> >>>>> >>>>> -- >>>>> Thank you. >>>>> >>>>> Sincerely, >>>>> *Lakini Senanayaka.* >>>>> >>>>> >>>> >>> >>> >>> -- >>> Upul Bandara, >>> Associate Technical Lead, WSO2, Inc., >>> Mob: +94 715 468 345. >>> >> >> > > > -- > Thank you. > > Sincerely, > *Lakini Senanayaka.* > > -- Upul Bandara, Associate Technical Lead, WSO2, Inc., Mob: +94 715 468 345.
_______________________________________________ Dev mailing list Dev@wso2.org http://wso2.org/cgi-bin/mailman/listinfo/dev
