I have been using SVM classifier with the following data
@relation whatever
@attribute mfe numeric
@attribute GB numeric
@attribute GTB numeric
@attribute Seeds numeric
@attribute ABP numeric
@attribute AU_Seed numeric
@attribute GC_Seed numeric
@attribute GU_Seed numeric
@attribute UP numeric
@attribute AU numeric
@attribute GC numeric
@attribute GU numeric
@attribute A-U_L numeric
@attribute G-C_L numeric
@attribute G-U_L numeric
@attribute (G+C) numeric
@attribute MFEi1 numeric
@attribute MFEi2 numeric
@attribute MFEi3 numeric
@attribute MFEi4 numeric
@attribute dG numeric
@attribute dP numeric
@attribute dQ numeric
@attribute dD numeric
@attribute Outcome {Yes,No}
@data
-24.3,1,18,2,9,4,3,0.5,8,10,7,1,0.454545455,0.318181818,0.045454545,7,-0.157792208,-0.050206612,-1.104545455,-1.35,-1.104545455,0,0,0,Yes
-24.8,2,15,2,7.5,2,3,1,7,5,8,2,0.208333333,0.333333333,0.083333333,8,-0.129166667,-0.043055556,-0.516666667,-1.653333333,-1.033333333,0,0,0,No
-24.4,1,16,3,5.333333333,1.666666667,2.666666667,1,4,5,8,3,0.217391304,0.347826087,0.130434783,8,-0.132608696,-0.046124764,-1.060869565,-1.525,-1.060869565,0,0,0,Yes
-24.2,1,18,2,9,2,2.5,1,10,5,11,2,0.227272727,0.5,0.090909091,11,-0.1,-0.05,-1.1,-1.344444444,-1.1,0,0,0,Yes
-24.5,3,17,2,8.5,2,3,1,5,6,9,2,0.272727273,0.409090909,0.090909091,9,-0.123737374,-0.050619835,-0.371212121,-1.441176471,-1.113636364,-0.12244898,0,0,Yes
This is my training set . And in this its defined whether my data is yes class or no class. My question is my test data is from unknown source and i dont have idea to what class it belongs. so how to prepare my test set. without the outcome attribute weka is giving the "ereor: Data mismatch " . How to prepare the test set? to separate my variable as Yes and nO class using SVM.
1-Open the "train" dataset in Weka. Next, choose "class" as the class attribute ("Preprocess" tab) 3-Click at the "Classify" tab. Once more, I had to choose "class" as the class attribute (I selected just below the "More Options" button). 5-Click at option "Supplied Test Set" and select your "test" dataset.
The Weka Experimenter allows you to design your own experiments of running algorithms on datasets, run the experiments and analyze the results. It’s a powerful tool. 3. Design Experiment Click the “ New ” button to create a new experiment configuration. The experimenter configures the test options for you with sensible defaults.
Set the connection string to your database, set up the query for data selection, process the query and load the selected records in WEKA. WEKA supports a large number of file formats for the data. Here is the complete list −
You would select an algorithm of your choice, set the desired parameters and run it on the dataset. Then, WEKA would give you the statistical output of the model processing. It provides you a visualization tool to inspect the data. The various models can be applied on the same dataset.
Steps to prepare the test set:
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