c# - Encog :"The Machine Learning Method has an input length of 7, but the training has 0" error -


i'm having project in use encog(.net) classify emg signal, features extracted, when try train it, gets error title says. here code use :

        basicnetwork jst = new basicnetwork();         jst.addlayer(new basiclayer(7));         jst.addlayer(new basiclayer(new activationsigmoid(), true, 10));         jst.addlayer(new basiclayer(new activationlinear(), true, 4));         jst.structure.finalizestructure();         jst.reset();          openfiledialog1.title = "open feature file...";         openfiledialog1.filename = "";         openfiledialog1.filter = "csv (comma delimited)|*.csv|all files|*.*";         if (openfiledialog1.showdialog() == dialogresult.cancel)         {             messagebox.show("choice cancelled");         }         else         {             iversatiledatasource data = new csvdatasource(openfiledialog1.filename, false, csvformat.decimalcomma);             var inputjst = new versatilemldataset(data);             inputjst.definesourcecolumn("mav", 0, encog.ml.data.versatile.columns.columntype.continuous);             inputjst.definesourcecolumn("rms", 1, encog.ml.data.versatile.columns.columntype.continuous);             inputjst.definesourcecolumn("var", 2, encog.ml.data.versatile.columns.columntype.continuous);             inputjst.definesourcecolumn("sd", 3, encog.ml.data.versatile.columns.columntype.continuous);             inputjst.definesourcecolumn("wl", 4, encog.ml.data.versatile.columns.columntype.continuous);             inputjst.definesourcecolumn("zc", 5, encog.ml.data.versatile.columns.columntype.continuous);             inputjst.definesourcecolumn("ssc", 6, encog.ml.data.versatile.columns.columntype.continuous);             columndefinition outputcolumn = inputjst.definesourcecolumn("arrow", 7, columntype.nominal);             inputjst.definesingleoutputothersinput(outputcolumn);             inputjst.analyze();              var model = new encogmodel(inputjst);             model.selectmethod(inputjst, mlmethodfactory.typefeedforward);             inputjst.normalize();              var train = new levenbergmarquardttraining(jst, inputjst);

my question why dataset have inputsize , idealsize 0, eventhough calculated size correct?

thanks.

after buzzing around codes, solutions, save normalized dataset csv, reload csvmldataset.

if wonders why not using csv normalizer, because result undesired (equilateral).

ps : have other solution still apreciated, thanks.


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