DMData Mining Techniques
All experiments

Experiment 07

Implement Decision Tree Classifier Using J48 (C4.5) in WEKA

Aim

To understand and implement decision tree classifier (j48) in weka using WEKA data mining tool.

Procedure

  1. Open WEKA → Launch weka.jar.
  2. Select Explorer.
  3. Load dataset → Click Open file... and choose a dataset (.arff or .csv). Example: iris.arff.
  4. Go to the Classify tab.
  5. Under Classifier → Choose, expand trees → select J48.
  6. (Optional) Configure J48 parameters:
    • -C <value>: Confidence factor for pruning (default 0.25).
    • -M <num>: Minimum number of instances per leaf (default 2).
  7. Select Test options (cross-validation, percentage split, or supplied test set).
  8. Click Start → WEKA will output the decision tree and accuracy.

Output

Implement Decision Tree Classifier Using J48 (C4.5) in WEKA output screenshot 1Implement Decision Tree Classifier Using J48 (C4.5) in WEKA output screenshot 2Implement Decision Tree Classifier Using J48 (C4.5) in WEKA output screenshot 3

Result

The experiment was successfully executed, and the expected output was obtained using WEKA.