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--- dm:mains.santanna.2011-12 [07/03/2013 alle 16:25 (12 anni fa)] – [Exercises] Fosca Giannotti
+++ dm:mains.santanna.2011-12 [14/03/2013 alle 15:03 (12 anni fa)] (versione attuale) – [Exercise] Deadline extended Fosca Giannotti
@@ Linea 50: / Linea 50: @@
 ===== Exercise =====
-  * **Breast Cancer Wisconsin (Diagnostic) Data Set. Assigned on: 07.03.2013. To be completed within: 18.03.2013. Send papers (3 pages max of text, figures excluded) by email to [[pedre@di.unipi.it]] cc: Fosca Giannotti[[fosca.giannotti@gmail.com]]. Use "[DM-MAINS] " in the subject. ** Download the {{http://archive.ics.uci.edu/ml/datasets/Breast+Cancer+Wisconsin+%28Diagnostic%29|wpbc.data dataset}} from the UCI archive. The dataset contains observations on samples of breast tissue, together with their classification as benign or malignant, as performed by istologists. You are supposed to perform the following tasks: 1) Data understanding and exploratory analysis; 2) clustering analysis (disregarding the class information), including description of the discovered (best) clusters; 3) classification analysis using decision trees for the task of diagnosing a sample as benign or malignant. Describe the process adopted to select the proposed clustering/tree, together with their quality evaluation.
+  * **Breast Cancer Wisconsin (Diagnostic) Data Set. Assigned on: 07.03.2013. To be completed within: 22.03.2013. Send papers (3 pages max of text, figures excluded) by email to [[pedre@di.unipi.it]] cc: Fosca Giannotti[[fosca.giannotti@gmail.com]]. Use "[DM-MAINS] " in the subject. Groupwork allowed, max 3 people per group, inter-disciplinary competence required in each group!**
+  * **Instructions:** Download the {{http://archive.ics.uci.edu/ml/datasets/Breast+Cancer+Wisconsin+%28Diagnostic%29|Wisconsin Diagnostic Breast Cancer (WDBC) dataset}} from the UCI archive. The dataset contains 569 observations on samples of breast tissue, together with their classification as benign or malignant, as performed by istologists. You are supposed to perform the following tasks: 1) Data understanding and exploratory analysis; 2) clustering analysis (disregarding the class information), including description of the discovered (best) clusters; 3) classification analysis using decision trees for the task of diagnosing a sample as benign or malignant. Describe the process adopted to select the proposed clustering/tree, together with their quality evaluation.
 ====== Exams ======
-For MAINS master students (one-year degree) the exam of the Data Mining module consists in the evaluation of the report of assigned exercises. For students of the two-year LM-MAINS degree the exam consists in the evaluation of the report of exercises, and an individual oral exam devoted to the discussion of aspects emerging from the exercises. The evaluation of the reports is the same for all components of the group (max 3 students oer group). The date of the first oral exam session of the LM-MAINS students will set by appointment.
+The exam of the Data Mining module consists in the evaluation of the report of assigned exercises. For students of the two-year LM-MAINS degree the exam consists in the evaluation of the report of exercises, and an individual oral exam devoted to the discussion of aspects emerging from the exercises. The evaluation of the reports is the same for all components of the group (max 3 students oer group). The date of the first oral exam session of the LM-MAINS students will set by appointment.
 ====== 2012 Edition ======