Logo Questions Linux Laravel Mysql Ubuntu Git Menu
 

Weka : How to prepare test set in weka

Tags:

weka

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.

like image 585
ramko Avatar asked Aug 08 '13 04:08

ramko


People also ask

How do I create a test set in Weka?

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.

How to design your own experiments in Weka?

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.

How to load the selected records in Weka?

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 −

How to use weka in machine learning?

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.


1 Answers

Steps to prepare the test set:

  1. Create a training set in CSV format.
  2. Also create the test set in CSV format with same no. of attributes and same type.
  3. Copy the test set and paste at the end of the training set and save as new CSV file.
  4. Import the saved CSV file in step 3 using Weka>>Explorer>>Preprocess.
  5. In Filter Option Choose filters>>unsupervised>>instances>>Remove Range.
  6. Click the feed which says RemoveRange-R first-last.
  7. Specify the range you want to remove say the training data had 100 values, then select first-100 and Apply the filter.
  8. Save as Arff file and this can be used as a test set.
  9. Then Apply this set. If you still have any errors, write as a reply to this post.
like image 136
Rajendra Kumar Avatar answered Oct 06 '22 00:10

Rajendra Kumar