Differenze

Queste sono le differenze tra la revisione selezionata e la versione attuale della pagina.

--- digitalhealth:0001a [08/12/2025 alle 10:39 (11 giorni fa)] – [First Semester] Anna Monreale
+++ digitalhealth:0001a [16/12/2025 alle 16:13 (2 giorni fa)] (versione attuale) – [Exams] Anna Monreale
@@ Linea 57: / Linea 57: @@
   * The slides used in the course will be inserted in the calendar after each class. Most of them are part of the slides provided by the textbook's authors [[http://www-users.cs.umn.edu/~kumar/dmbook/index.php#item4|Slides per "Introduction to Data Mining"]].
+===== Past Excercises and past exams of similar courses  =====
+  * Exercises on Clustering: {{ :dm:ex._clustering.pdf |}}
+  * Excercise for DT learning simulation: {{ :magistraleinformatica:dmi:dt-learning-simulation.pdf |}} {{ :magistraleinformatica:dmi:learnedtree.pdf |}}
+  * Some text of past exams of a similar course: {{ :dm:2017-1-19.pdf |}}, {{ :dm:2017-9-6.pdf |}}, {{ :dm:2016-05-30-dm1-seconda.pdf |}}, {{ :dm:dm2_exam.2017.06.13_solutions.pdf |}}, {{ :dm:dm2_exam.2017.07.04_solutions.pdf |}}, {{ :dm:dm2_mid-term_exam.2017.06.06_solutions.pdf |}}, {{ :dm:dm2_exam.2015.04.13.results.pdf|}}, {{ :dm:dm2_exam.2016.04.4_sol.pdf |}}, {{ :dm:dm2_exam.2016.04.5_sol.pdf |}}, {{ :dm:dm2_exam.2016.06.20_sol.pdf |}}, {{ :dm:dm2_exam.2016.07.08_sol.pdf |}}
+   * Some very old exercises (part of them with solutions) are available here, most of them in Italian, not all of them on topics covered in this year program: {{tdm:verifica2006.pdf|Verifica 2006}}, {{tdm:verifica2005.pdf|Verifica 2005 (con soluzioni)}}, {{tdm:verifica2004.pdf|Verifica 2004}}, {{dm:verifica.05.06.2007.pdf|Verifica 5 giugno 2007}}, {{dm:verifica.26.06.2007.pdf|Verifica 26 giugno 2007}}, {{dm:verifica.24.07.2007_corretto.pdf|Verifica 24 luglio 2007}} (e {{:dm:soluzioni.2008.04.03.pdf|Soluzioni}}), {{:dm:dm-tdm.appello_2008_07_18_parte1.pdf|Verifica 18 luglio 2008 - parte 1}}, {{:dm:dm-tdm.appello_2008_07_18_parte2.pdf|Verifica 18 luglio 2008 - parte 2}},{{:dm:appello.2010.06.01_soluzioni.pdf| Exam with solution 2010-06-01}},{{:dm:appello.2010.06.22_soluzioni.pdf|Exam with solution 2010-06-22}}, {{:dm:appello.2010.09.09_soluzioni.pdf|Exam with solution 2010-09-09}},{{:dm:appello.2010.07.13_soluzioni.pdf| Exam with solution 2010-07-13}}
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 ====== Class Calendar (2025/2026) ======
+c
 ===== First Semester  =====
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 |26.  | 24.11 |Imbalanced learning  | {{:digitalhealth:imbalanced-learning.pdf}}| | |
 |27.  | 25.11 | Python Lab on classification and presentation of the project, task 4|{{:digitalhealth:classification-diabetes.ipynb.zip}}{{:digitalhealth:imbalanced-classification.zip}} | |Naretto |
-|28.  | 28.11 |GSP and Apriori | | |Monreale |
+|28.  | 28.11 |GSP and Apriori |{{:digitalhealth:18_sequential_patterns_2024.pdf}} | |Monreale |
-|29.  | 01.12 |GSP and Apriori | | |Monreale |
+|29.  | 01.12 |GSP and Apriori |{{:digitalhealth:17_association_analysis.pdf}} | |Monreale |
-|30.  | 02.12 |Time series |{{:digitalhealth:digitalhealth:23_time_series_motif-2024.pdf}} | |Monreale |
+|30.  | 02.12 |Time series |{{:digitalhealth:23_time_series_motif-2024.pdf}}{{:digitalhealth:matrixprofile.pdf}} {{ :digitalhealth:shaplets.pdf |}}| |Monreale |
-|31.  | 05.12 |Time series lab |{{:digitalhealth:digitalhealth:23_time_series_motif-2024.pdf}} | |Naretto |
+|31.  | 05.12 |Time series lab |{{:digitalhealth:23_time_series_motif-2024.pdf}} | |Naretto |
-|32.  | 09.12 | | | | |
+|32.  | 09.12 |Anomaly detection tabular data |{{:digitalhealth:21_anomaly_detection_2020.pdf}} | |Naretto |
-|33.  | 12.12 | | | | |
+|  | 12.12 |Strike | | | |
-|34.  | 15.12 | | | | |
+|33.  | 15.12 |Anomaly detection ts + Python lab |{{:digitalhealth:21_anomaly_detection_2020.pdf}} {{digitalhealth:anomalydetection-1.ipynb.zip}} | | Naretto |
-|35.  | 16.12 | | | | |
+|34.  | 16.12 | | | | |
-|36.  | 19.12 | Project CHECK - mandatory | | | |
+|35.  | 19.12 | Project CHECK - mandatory | | | |
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 A project consists in data analyses based on the use of data mining tools.
 The project has to be performed by a team of 2 max 3 students. It has to be performed by using Python. The guidelines require to address specific tasks. Results must be reported in a unique paper. The total length of this paper must be max 25 pages of text including figures. The students must deliver both: paper (single column) and  well commented Python Notebooks.
+Deadline. January 5th, 2026.
+Delivery instructions. The final deadline of the project is 5th January 2026 at 23:59. This deadline is STRICT. No extension is possible because then the winter session of exams starts. Groups that will not deliver the project by 5th January will need to do the written exam during the exam sessions. Each group must deliver by email to anna.monreale@unipi.it, francesca.naretto@unipi.it a zipped folder named DM_GroupID.zip and containing 4 folders and 1 pdf file: a folder named DM_GroupID_TASK_DU, containing source code of data understanding; a folder named DM_GroupID_TASK_CLU, containing source code of data clustering; a folder named DM_GroupID_TASK_CLA, containing source code of classification; a folder named DM_GroupID_TASK_TS, containing source code of time series analysis; a pdf file with maximum 25 pages including figures discussing the results of the tasks. The name of this file must be: DM_Report_GroupID.pdf. The file must contain the list of authors (i.e., members of the group). The subject of the email must be “DADHProject25_GroupID”
 ====== Previous years =====