1. Data Understanding: Understand the dataset and its features.
2. Data Preprocessing: Clean and prepare the data for training.
3. Induce: Use divide and conquer to recursively split the training set.
4. Tree Pruning: Trim the tree to avoid overfitting.
5. Production Rule Extraction: Extract rules from the pruned tree.
6. Predictive Model Application:
   • Predict using the pruned tree.
   • Predict using the extracted rule set.
7. Explanation Tool Usage: The rule covering a new instance serves as an explanation for the prediction.

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