| Entrambe le parti precedenti la revisioneRevisione precedenteProssima revisione | Revisione precedente |
| magistraleinformatica:dmi:start [21/10/2025 alle 08:35 (2 settimane fa)] – [First Semester] Anna Monreale | magistraleinformatica:dmi:start [05/11/2025 alle 18:44 (69 minuti fa)] (versione attuale) – [First Semester] Anna Monreale |
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| | 10. | 15.10 | Anomaly detection | {{ https://github.com/data-mining-UniPI/teaching25/blob/lectures/anomaly%20detection/Anomaly%20detection.html.pdf | Slides }} | | Setzu | | | 10. | 15.10 | Anomaly detection | {{ https://github.com/data-mining-UniPI/teaching25/blob/lectures/anomaly%20detection/Anomaly%20detection.html.pdf | Slides }} | | Setzu | |
| | 11. | 16.10 | Anomaly detection | {{ https://github.com/data-mining-UniPI/teaching25/blob/lectures/anomaly%20detection/Anomaly%20detection.html.pdf | Slides }}, {{ https://github.com/data-mining-UniPI/teaching25/blob/main/notebooks/outliers.ipynb | Notebook }}, {{ https://github.com/data-mining-UniPI/teaching25/blob/main/notebooks/isolation_forest.py | Rule extraction from isolation forests }} | | Setzu | | | 11. | 16.10 | Anomaly detection | {{ https://github.com/data-mining-UniPI/teaching25/blob/lectures/anomaly%20detection/Anomaly%20detection.html.pdf | Slides }}, {{ https://github.com/data-mining-UniPI/teaching25/blob/main/notebooks/outliers.ipynb | Notebook }}, {{ https://github.com/data-mining-UniPI/teaching25/blob/main/notebooks/isolation_forest.py | Rule extraction from isolation forests }} | | Setzu | |
| |12. | 21.10 | Variants of K-means + Association Rule Mining | {{ :magistraleinformatica:dmi:11-basic_cluster_analysis-kmeans-variants.pdf |}} | | Monreale | | |12. | 21.10 | Variants of K-means + Association Rule Mining | {{ :magistraleinformatica:dmi:11-basic_cluster_analysis-kmeans-variants.pdf |}} {{ :magistraleinformatica:dmi:17_association_analysis2023.pdf |}} | | Monreale | |
| | |13. | 22.10 | Association Rule Mining: Apriori | {{ :magistraleinformatica:dmi:17_association_analysis2023.pdf |}} | | Monreale | |
| | |14. | 23.10 | Association Rule Mining: CORELS | {{ https://github.com/data-mining-UniPI/teaching25/blob/lectures/rule_mining/Rule%20extraction.html.pdf | Slides }}, {{ https://corels.cs.ubc.ca/corels/index.html | Online tool }} | | Setzu | |
| | |15. | 28.10 | Visual Analytcs | {{ :magistraleinformatica:dmi:dm_intro_dataviz_vegaaltair.pdf |Slides}} {{ :magistraleinformatica:dmi:1_bis_basics_and_understanding_altair.ipynb.zip | Code for data visualization with Altair}}| |Monreale, Rinzivillo| |
| | |16. | 29.10 | Association Rule Mining: FP-Growth + Sequential Pattern Mining| {{ :magistraleinformatica:dmi:17_2023-fp-growth.pdf |FP-Growth}}{{ :magistraleinformatica:dmi:18_sequential_patterns_2024.pdf |SPM}}| |Monreale| |
| | | | 30.10 | Lecture is canceled| | | | |
| | |17. | 04.11 | Sequential Pattern Mining with time constraints + Python Lab: FPM + SPM.| For SPM the same set of slides used in the previous lecture {{ :magistraleinformatica:dmi:5_patternmining.ipynb.zip |}} | |
| | |18. | 05.11 | Supervised learning and classification | {{ :magistraleinformatica:dmi:supervisinglearning.pdf | Slides}}| | Setzu | |
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