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What are nominal attributes in Weka?

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What are nominal attributes in Weka?

nominal: This type of attribute represents a fixed set of nominal values. String attributes are not used by the learning schemes in Weka. They can be used, for example, to store an identifier with each instance in a dataset.

What are filters in Weka?

Weka include many filters that can be used before invoking a classifier to clean up the dataset, or alter it in some way. Filters help with data preparation. For example, you can easily remove an attribute.

What is class attribute in data mining?

To predict a classification, you must specify the input fields to be classified and the class label field. The class label field contains the class labels of the classes to which the records in the source data were attributed during the historical classification. …

How can we reduce dataset in Weka?

Select Attributes in Weka

  1. Click the “Preprocess” tab.
  2. In the “Attributes” selection Tick all but the plas, pres, mass, age and class attributes. Weka Select Attributes To Remove From Dataset.
  3. Click the “Remove” button.
  4. Click the “Save” button and enter a filename.

How do you normalize in Weka?

Normalize Your Numeric Attributes

  1. Open the Weka Explorer.
  2. Load your dataset.
  3. Click the “Choose” button to select a Filter and select unsupervised.
  4. Click the “Apply” button to normalize your dataset.
  5. Click the “Save” button and type a filename to save the normalized copy of your dataset.

How does Weka clean data?

Step 1: Data Pre Processing or Cleaning

  1. Launch Weka-> click on the tab Explorer.
  2. Load a dataset. (
  3. Click on PreProcess tab & then look at your lower R.H.S. bottom window click on drop down arrow and choose “No Class”
  4. Click on “Edit” tab, a new window opens up that will show you the loaded datafile.

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