Data-Mining-2020-2021-Project-Group24-customer_supermarket 1. Data Understanding and Preparation 1.1 Data semantics 1.2 Assessing data quality 1.3 Distribution of the variables and statistics 1.4 Variables transformations and generation 1.5 Preliminary observations 1.6 Exploring the new features for a statistical analysis 2. Clustering Analysis 2.1 K-means 2.2 Density based clustering 2.3 Hierarchical clustering 2.4 K-Medoids (optional task) 2.5 Final evaluation of the best clustering approach and comparison of the clustering obtained 3. Classification 3.1 Data preparation 3.2 Performing prediction using various different classification algorithms 3.3 Model comparisons 4. Sequential Pattern Mining 4.1 Data preparation 4.2 Mining sequential patterns 4.3 Results discussion and mining sequential patterns through categorizing products 4.4 Sequential pattern mining with temporal constraints 5. Conclusion