Data Mining

Preparing and preprocessing the data 3. Finding rules, including appropriate parameter setting 4. Determining which of the resulting rules are interesting 5. Figuring out how the interesting rules could be useful 1. Objectives: What is the domain and what are the potential benefits to be derived from association rule mining. This is high level - not find patterns, but what would improve because of the use of the patterns. 2. Data set description: What is in the data, and what preprocessing was done to make it amenable for association rule mining. Where choices were made (e.g., parameter settings for discretization, or decisions to ignore an attribute), describe your reasoning behind the choices. 3. Rule mining process: Parameter settings, choice of algorithm and the time required. Using a dataset from the link : [login to view URL] Should be Documented