CODEWITHSUNDEEP
weka
Dattaprasad
Dattaprasad

Reputation: 105

Empty confusion matrix in Weka with test data

I am classifying iris data using DECISION TREE (C4.5), RANDOM FOREST and NAIVE BAYES. I am using the dataset downloaded from iris-train and iris-test. When I train the all networks everything is fine with proper results with 'classifier output', 'Detailed accuracy with class' and 'confusion matrix'. But, when I select the iris-test data in the Weka-explorer-classify-test options and select the iris-test file and in 'more options' select 'output prediction' as 'csv' and click start, I am getting the result as shown in the figure below. Weka output The 'classifier output' is showing the classified samples correctly, but, 'Detailed accuracy with class' and 'confusion matrix' is with all values zeros. Any suggestion where I am going wrong in selecting any option. Thank you.

Upvotes: 0

Views: 1425

Answers (1)

nekomatic
nekomatic

Reputation: 6284

The confusion matrix shows you how well your trained classifier performs by comparing the actual class of the instances in the test set with the class that was predicted by the classifier. But you are supplying a test set with no class information, so there's nothing to compare against. This is why you see

Total Number of Instances         0
Ignored Class Unknown Instances   120

in the output in your screenshot.

Typically you would first evaluate the performance of your classifier using cross-validation, or a test set that has class information. Then you can use the trained classifier to classify unknown data, for example using the Re-evaluate model on current test set right-click option as described in the help.

Upvotes: 1

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