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dm:start [05/12/2022 alle 10:59 (16 mesi fa)] Riccardo Guidotti [First Semester (DM1 - Data Mining: Foundations)] |
dm:start [26/03/2024 alle 17:16 (44 ore fa)] (versione attuale) Riccardo Guidotti [Second Semester (DM2 - Data Mining: Advanced Topics and Applications)] |
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- | ====== Data Mining A.A. 2022/23 ====== | + | ====== Data Mining A.A. 2023/24 ====== |
===== DM1 - Data Mining: Foundations (6 CFU) ===== | ===== DM1 - Data Mining: Foundations (6 CFU) ===== | ||
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Teaching Assistant | Teaching Assistant | ||
- | * **Francesco Spinnato** | + | * **Andrea Fedele** |
- | * KDDLab, | + | * KDDLab, |
- | * [[https://kdd.isti.cnr.it/people/spinnato-francesco]] | + | * [[https://www.linkedin.com/in/andrea-fedele/? |
- | * [[francesco.spinnato@sns.it]] | + | * [[andrea.fedele@phd.unipi.it]] |
===== DM2 - Data Mining: Advanced Topics and Applications (6 CFU) ===== | ===== DM2 - Data Mining: Advanced Topics and Applications (6 CFU) ===== | ||
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Teaching Assistant | Teaching Assistant | ||
- | * **Francesco Spinnato** | + | * **Andrea Fedele** |
- | * KDDLab, | + | * KDDLab, |
- | * [[https://kdd.isti.cnr.it/people/spinnato-francesco]] | + | * [[https://www.linkedin.com/in/andrea-fedele/? |
- | * [[francesco.spinnato@sns.it]] | + | * [[andrea.fedele@phd.unipi.it]] |
+ | * Meeting: https:// | ||
====== News ====== | ====== News ====== | ||
- | * [15.09.2022] Project Groups [[https:// | + | |
- | * [15.09.2022] MS Teams [[https:// | + | * **[19.01.2024]** DM2 Lectures will start on Mon 19/02, only for that lecture the time will be 14-16 instead of 9-11. |
- | * [15.09.2022] Lectures will be in presence only. Registrations of the lectures of past years can be found at the bottom of this web page. | + | * [13.10.2023] To schedule meeting with the Teaching Assistant you can use: https:// |
- | * **[23.11.2022]** In order to recover from skipped and suspended lectures we signal the presence of two new dates in unusual slots for our lectures, i.e., Wed 7th Dec 14.00-16.00 Room A1 and Wed 14th Dec 14.00-16.00 Room A1. | + | * [20.09.2023] Recordings of the lectures can be found on the web pages of the course for the years 2020/2021 and 2021/2022 (see links at the bottom of this page) |
+ | * [20.09.2023] Thursday 21 September there will be no lecture. | ||
+ | * [11.09.2023] Lectures will start on Monday 18 September 2023 at 11.00 room C1. | ||
+ | * [11.09.2023] Lectures will be in presence only. Registrations of the lectures of past years can be found at the bottom of this web page. | ||
+ | * [11.09.2023] Project Groups [[https:// | ||
+ | * [11.09.2023] MS Teams [[https:// | ||
====== Learning Goals ====== | ====== Learning Goals ====== | ||
* DM1 | * DM1 | ||
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^ Day of Week ^ Hour ^ Room ^ | ^ Day of Week ^ Hour ^ Room ^ | ||
- | | Monday | + | | Monday |
- | | | + | | |
**Office hours - Ricevimento: | **Office hours - Ricevimento: | ||
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* Online | * Online | ||
* Prof. Guidotti | * Prof. Guidotti | ||
- | * Wednesday 15-17 or Appointment by email | + | * Tuesday 16:00 - 18:00 or Appointment by email |
* Room 363 Dept. of Computer Science or MS Teams | * Room 363 Dept. of Computer Science or MS Teams | ||
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^ Day of Week ^ Hour ^ Room ^ | ^ Day of Week ^ Hour ^ Room ^ | ||
- | | | + | | |
- | | | + | | |
**Office Hours - Ricevimento: | **Office Hours - Ricevimento: | ||
- | * Wednesday | + | * Tuesday |
* Room 363 Dept. of Computer Science or MS Teams | * Room 363 Dept. of Computer Science or MS Teams | ||
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* [[http:// | * [[http:// | ||
* [[http:// | * [[http:// | ||
- | * Didactic Data Mining [[http:// | + | * Didactic Data Mining [[http:// |
- | ====== Class Calendar (2021/2022) ====== | + | ====== Class Calendar (2023/2024) ====== |
===== First Semester (DM1 - Data Mining: Foundations) ===== | ===== First Semester (DM1 - Data Mining: Foundations) ===== | ||
- | ^ ^ Day ^ Time ^ Room ^ Topic ^ Learning | + | ^ ^ Day ^ Time ^ Room ^ Topic ^ Material ^ Lecturer ^ |
- | |01.| 15.09.2022 | 11-13 |A1| Overview, | + | |01.| 18.09.2023 | 11-13 |C1| Overview, |
- | | | + | | |
- | |02.| 22.09.2022 | 11-13 |A1| Project Guideliens & Intro to Python | {{ : | + | |02.| 25.09.2023 | 11-13 |C1| Lab. Introduction |
- | | | 26.09.2022 | 11-13 | | No Lecture | | | + | |03.| 27.09.2023 | 11-13 |C1| Lab. Data Understanding | {{ :dm:dm1_lab02_data_understanding.zip | Data Understanding}} | Guidotti| |
- | |03.| 29.09.2022 | 11-13 |A1| Data Understanding | {{ :dm:01_dm1_data_understanding_2022_23.pdf | Data Understanding}} | + | |04.| 02.10.2023 | 11-13 |C1| Data Understanding | {{ :dm:01_dm1_data_understanding_2023_24.pdf | Data Understanding}} | Guidotti| |
- | |04.| 03.10.2022 | 11-13 |A1| Data Understanding | + | |05.| 04.10.2023 | 11-13 |C1| Data Understanding |
- | |05.| 06.10.2022 | 11-13 |A1| Lab. Data Understanding | {{ :dm:data_understanding.zip | Data Und Python}} | Spinnato/ | + | |06.| 09.10.2023 | 11-13 |C1| Data Preparation |
- | | | 10.10.2022 | + | |07.| 11.10.2023 | 11-13 |C1| Data Similarity & Lab. Data Understanding |
- | |06.| 13.10.2022 | 11-13 |A1| Data Preparation, Similarity | {{ :dm:03_dm1_data_similarity_2022_23.pdf | Data Similarity}}, {{ :dm:data_understanding.zip | Data Und Python}} | Pedreschi | | + | |08.| 16.10.2023 | 11-13 |C1| Introduction to Clustering, |
- | |07.| 17.10.2022 | 11-13 |A1| Intro Clustering, K-Means | + | |09.| 18.10.2023 | 11-13 |C1| Clustering Validation, |
- | |08.| 20.10.2022 | 11-13 |A1| K-Means | {{ :dm:05_dm1_kmeans_2022_23.pdf | K-Means}} | Pedreschi | | + | |10.| 23.10.2023 | 11-13 |C1| Density-based |
- | |09.| 24.10.2022 | 11-13 |A1| Hierarchical | + | |11.| 25.10.2023 | 11-13 |C1| Lab. Clustering |
- | |10.| 27.10.2022 | 11-13 |A1| Lab. Clustering | {{ :dm:clustering.zip | Clustering | + | |12.| 30.10.2023 | 11-13 |C1| Ex. Clustering | {{ :dm:ex1_dm1_clustering_2023_24.pdf | ExClustering}}| Guidotti| |
- | | | + | | | 01.11.2023 | 11-13 | | No Lecture | | | |
- | |11.| 03.11.2022 | 11-13 |A1| Exercises | + | |13.| 06.11.2023 | 11-13 |C1| Intro Classification, kNN[[https:// |
- | |12.| 07.11.2022 | 11-13 |A1| Intro Classification | {{ :dm:08_dm1_classification_intro_2022_23.pdf | Intro Classification}}, {{ :dm:09_dm1_knn_2022_23.pdf | kNN}} | Guidotti | | + | |14.| 08.11.2023 | 11-13 |C1| Naive Bayes, Exercises | {{ :dm:10_dm1_naive_bayes_2023_24.pdf | Naive Bayes}} | Guidotti| |
- | |13.| 10.11.2022 | 11-13 |A1| Eval Measures, Exercises | + | |15.| 13.11.2023 | 11-13 |C1| Model Evaluation |
- | |14.| 14.11.2022 | 11-13 |A1| Decision Tree | {{ :dm:10_dm1_decision_trees_2022_23.pdf | Decision Trees}} | Guidotti | | + | |16.| 15.11.2023 | 11-13 |C1| Model Evaluation |
- | |15.| 17.11.2022 | 11-13 |A1| Decision Tree, Exercises | + | | | 20.11.2023 |
- | |16.| 22.11.2022 | 11-13 |A1| Decision Tree | {{ :dm:10_dm1_decision_trees_2022_23.pdf | Decision | + | |17.| 22.11.2023 | 11-13 |C1| Decision Tree Classifier |
- | |17.| 24.11.2022 | 11-13 |A1| Naive Bayes Classifier | {{ :dm:11_dm1_naive_bayes_2022_23.pdf | NBC}} | Guidotti | + | |18.| 27.11.2023 | 11-13 |C1| Decision Tree Classifier | {{ :dm:12_dm1_decision_trees_2023_24.pdf | Decision Tree}} | Pedreschi| |
- | |18.| 28.11.2022 | 11-13 |A1| Lab. Classification | + | |19.| 29.11.2023 | 11-13 |C1| Exercises and Lab. Decision Tree Classifier |
- | |19.| 01.12.2022 | 11-13 |A1| Intro Regression | + | |20.| 04.12.2023 | 11-13 |C1| Decision Tree Classifier, Exercises and Lab | {{ :dm:12_dm1_decision_trees_2023_24.pdf | Decision Tree}} | Pedreschi| |
- | |20.| 05.12.2022 | 11-13 |A1| Pattern Mining | + | |21.| 06.12.2023 | 11-13 |C1| Intro Regression & Lab. Regression |
- | |21.| 07.12.2022 | 14-16 |A1| Pattern Mining | | Pedreschi | | + | |22.| 11.12.2023 | 11-13 |C1| Into Pattern Mining |
- | | | 08.12.2022 | + | |23.| 13.12.2023 | 16-18 |C1| Apriori & Lab. Pattern Mining |
- | |22.| 12.12.2022 | + | |24.| 18.12.2023 | 11-13 |C| FP-Growth and Exercises | {{ : |
- | |23.| 14.12.2022 | 14-16 |A1| TBD | | Guidotti | + | |
- | |24.| 15.12.2022 | 11-13 |A1| Lab. Pattern Mining | | Spinnato/Guidotti | | + | |
===== Second Semester (DM2 - Data Mining: Advanced Topics and Applications) ===== | ===== Second Semester (DM2 - Data Mining: Advanced Topics and Applications) ===== | ||
- | ^ ^ Day ^ Room ^ Topic ^ Learning | + | ^ ^ Day ^ Time ^ Room ^ Topic ^ Material ^ Lecturer |
- | | 01.| 14.02.2022 11:00--13:00 | C | | | Guidotti | | + | |01.| 19.02.2024 |
+ | | | 21.02.2024 | | | No Lecture | | | | ||
+ | | | 26.02.2024 | | | No Lecture | | | | ||
+ | |02.| 19.02.2024 | 11-13 |C| Sequential Pattern Mining | {{ :dm: | ||
+ | |03.| 04.03.2024 | 9-11 |C| Sequential Pattern Mining | {{ : | ||
+ | |04.| 06.03.2024 | 11-13 |C| Transactional Clustering | {{ :dm: | ||
+ | |05.| 11.03.2024 | 9-11 |C| Time Series Similarity | ||
+ | |06.| 13.03.2024 | 11-13 |C| Time Series Approximation | {{ : | ||
+ | |07.| 18.03.2024 | 9-11 |C| Time Series Clustering & Motifs| {{ : | ||
+ | |08.| 20.03.2024 | 11-13 |C| Time Series Classification | {{ : | ||
+ | |09.| 25.03.2024 | 9-11 |C| Imbalanced Learning | {{ : | ||
+ | |10.| 27.03.2024 | 11-13 |C| Dimensionality Reduction | {{ : | ||
====== Exams ====== | ====== Exams ====== | ||
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** What: ** | ** What: ** | ||
The oral test will evaluate the practical understanding of the algorithms. The exam will evaluate three aspects. | The oral test will evaluate the practical understanding of the algorithms. The exam will evaluate three aspects. | ||
- | - Understanding of the theoretical aspects of the topics addressed during the course. The student may be required to write on formulas or pseudocode. During the explanations, | + | - Understanding of the theoretical aspects of the topics addressed during the course. The student may be required to write on formulas or pseudocode. During the explanations, |
- Understanding of the algorithms illustrated during the course and their practical implementation. You will be asked to perform one or more simple exercises. The text will be shown on the teacher' | - Understanding of the algorithms illustrated during the course and their practical implementation. You will be asked to perform one or more simple exercises. The text will be shown on the teacher' | ||
- Discussion of the project with questions from the teacher regarding unclear aspects, | - Discussion of the project with questions from the teacher regarding unclear aspects, | ||
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average mark of DM1 and DM2. | average mark of DM1 and DM2. | ||
- | **Exam Booking Periods** | + | ===== Exam Booking Periods |
* Exam portal link: [[https:// | * Exam portal link: [[https:// | ||
- | * 1st Appello: | + | * 1st Appello: |
- | * 2nd Appello: 01/01/2023 00:00 - 26/01/2023 23:59 | + | * 2nd Appello: |
+ | * 3rd Appello: | ||
+ | * 4th Appello: | ||
+ | * 5th Appello: | ||
+ | * 6th Appello: | ||
- | **Exam Booking Agenda** | + | ===== Exam Booking Agenda |
- | * Agenda Link: [[https:// | + | * 1st Appello - DM1: https:// |
- | * 1st Appello: | + | * 2nd Appello |
- | * 2nd Appello: | + | * 3rd Appello: |
+ | * 4th Appello: | ||
+ | * 5th Appello: | ||
+ | * 6th Appello: | ||
+ | |||
+ | **Do not forget to make the evaluation of the course!!!** | ||
===== Exam DM1 ====== | ===== Exam DM1 ====== | ||
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* An **oral exam**, that includes: (1) discussing the project report; (2) discussing topics presented during the classes, including the theory and practical exercises. | * An **oral exam**, that includes: (1) discussing the project report; (2) discussing topics presented during the classes, including the theory and practical exercises. | ||
- | * A **project**, | + | * A **project**, |
* **Dataset** | * **Dataset** | ||
- | - Assigned: | + | - Assigned: |
- | - MidTerm Submission: | + | - MidTerm Submission: |
- | - Final Submission: | + | - Final Submission: 31/12/2023 (+0.5) |
- | - Dataset: {{:dm:ravdess_dm1_2223.zip | RAVDESS}} | + | - Dataset: {{ :dm:std.zip | STD}} |
- | - Link original pages: [[https:// | + | |
** DM1 Project Guidelines ** | ** DM1 Project Guidelines ** | ||
- | See {{ :dm:dm1_project_guidelines_22_23.pdf | Project Guidelines}}. | + | See {{ :dm:dm1_project_guidelines_23_24.pdf | Project Guidelines}}. |
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===== Exam DM2 ====== | ===== Exam DM2 ====== | ||
- | TBD | + | The exam is composed of two parts: |
+ | |||
+ | * An **oral exam**, that includes: (1) discussing the project report; (2) discussing topics presented during the classes, including the theory and practical exercises. | ||
+ | |||
+ | * A **project**, | ||
+ | |||
+ | * **Dataset** | ||
+ | - Assigned: 19/ | ||
+ | - MidTerm Submission: 30/04/2024 (Modules 1 and 2 (for TS classification non DL-based models) | ||
+ | - Final Submission: one week before the oral exam (complete project required, also with DL-based models for TS classification). | ||
+ | - Dataset: [[https:// | ||
+ | |||
+ | ** DM2 Project Guidelines ** | ||
+ | See {{ : | ||
- | ====== Exam Dates ====== | ||
- | ===== Exam Sessions ===== | ||
- | ^ Session ^ Date ^ Room ^ Notes ^ Marks ^ | ||
- | |1.|10.01.2023| | Please, use the system for registration: | ||
- | |2.|31.01.2023| | Please, use the system for registration: | ||
- | |3.|?? | ||
- | |4.|?? | ||
- | |5.|?? | ||
- | |6.|?? | ||
===== Past Exams ===== | ===== Past Exams ===== | ||
* Past exams texts can be found in old pages of the course. Please do not consider these exercises as a unique way of testing your knowledge. Exercises can be changed and updated every year and will be published together with the slides of the lectures. | * Past exams texts can be found in old pages of the course. Please do not consider these exercises as a unique way of testing your knowledge. Exercises can be changed and updated every year and will be published together with the slides of the lectures. | ||
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====== Previous years ===== | ====== Previous years ===== | ||
+ | * [[dm.2022-23ds]] | ||
* [[dm.2021-22ds]] | * [[dm.2021-22ds]] | ||
* [[dm.2020-21]] | * [[dm.2020-21]] |