Explores Association Rule Mining, emphasizing Frequent Itemsets and Alternative Measures of Interest, including the FP-Growth algorithm and performance comparison.
Introduces association rule mining, covering support, confidence, Apriori algorithm, and FP-growth for frequent itemset discovery.
Covers association rules mining, focusing on Apriori and FP-growth algorithms to find frequent itemsets and extract rules efficiently.
Covers the challenges and opportunities of data mining, practical questions, algorithm components, and applications like shopping basket analysis.
