4. Repeat steps 2 and 3 for each and every leaf node until the stopping criteria is reached (e. g, the node is dominated by a single class label) Define gini index What does it measure? The Gini index and information gain(entropy) are two popular ways to determine branching choices in a decision tree. The Gini index measures the purity of sample. If everything in a sample belongs to one class, the gini index value is zero Give examples of situations in which cluster analysis would be an appropriate data mining technique Cluster algorithms are used when the data records do not have predefined class identifiers(i.e, it is not known to what class a particular record belongs) 8. What is the major difference between cluster analysis and classification? Classification methods learn from previous examples containing inputs and the resulting class labels, and once properly trained, they are able to classify future cases. Clustering partitions pattern records into natural segments or clusters What are some of the methods for cluster analysis? The most commonly used clustering algorithms are k-means and self-organizing maps 10. Give examples of situations in which association would be an appropriate data mining technique Association rule mining is appropriate to use when the objective is to discover two or more items(or events or concepts) that go together. Students' answers will differ 11. Give examples of situations in which association would be an appropriate data mining technique Examples include the following Sales transactions Cred it card transactions Banking services Insurance service products Telecommunication services Copyright C2018 Pearson Education, Inc.9 Copyright © 2018Pearson Education, Inc. 4. Repeat steps 2 and 3 for each and every leaf node until the stopping criteria is reached (e.g., the node is dominated by a single class label). 6. Define Gini index. What does it measure? The Gini index and information gain (entropy) are two popular ways to determine branching choices in a decision tree. The Gini index measures the purity of a sample. If everything in a sample belongs to one class, the Gini index value is zero. 7. Give examples of situations in which cluster analysis would be an appropriate data mining technique. Cluster algorithms are used when the data records do not have predefined class identifiers (i.e., it is not known to what class a particular record belongs). 8. What is the major difference between cluster analysis and classification? Classification methods learn from previous examples containing inputs and the resulting class labels, and once properly trained, they are able to classify future cases. Clustering partitions pattern records into natural segments or clusters. 9. What are some of the methods for cluster analysis? The most commonly used clustering algorithms are k-means and self-organizing maps. 10. Give examples of situations in which association would be an appropriate data mining technique. Association rule mining is appropriate to use when the objective is to discover two or more items (or events or concepts) that go together. Students’ answers will differ. 11. Give examples of situations in which association would be an appropriate data mining technique. Examples include the following: • Sales transactions • Credit card transactions • Banking services • Insurance service products • Telecommunication services