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Classify New Data



Classification is the process of using a trained classifier to predict the classes of the items in a dataset.



1. Click a raw or filtered dataset in the Experiments navigator. The item is highlighted.

2. Click the Classify toolbar icon , or select Classify from the Predict menu. The Classify dialog is displayed.

3. Set the parameters.




The name of the new item which will be seen in the Experiments navigator.


An optional description of the item.


The classifier to be used for the class prediction.


4. Click OK. The Experiment Progress dialog is displayed. It is dynamically updated as the Classify operation is performed. To cancel the Classify operation, click the Cancel button.

Upon successful completion, a new item (Name) is added under the original item in the Experiments navigator.


Reasons For Misclassifications:

There are often no misclassifications in the training data – artificial neural networks are fairly powerful and adaptable learners. If there are misclassifications, however, it may be for one of several possible reasons:

The above reasons may affect either training or test results. If the training results are excellent but the test results are poor, it may be for one of the following additional reasons:


Related Topics:

ANN Classification and Prediction Overview

Classifier Viewer

IBIS Overview