-
Data Understanding and Preparation
-
Clustering analysis
Based on the customer’s profile explore the dataset using various clustering techniques. Carefully describe your decisions for each algorithm and which are the advantages provided by the different approaches.
- Classification Analysis
Consider the problem of predicting for each customer a label that defines if (s)he is a high-spending customer, medium-spending customer or low-spending customer.
-
Sequential Pattern Mining
Consider the problem of mining frequent sequential patterns. To address the task: Model the customer as a sequence of baskets Apply the Sequential Pattern Mining algorithm (gsp implementation) Discuss the resulting patterns (optional) Handling time constraint while building Sequential Patterns