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Isra University 1 Faculty Information Technology Department of Computer Science Course Plan ________________________________________________________________________________________________ Course No.: 601323 Course Name: Data Mining Course Website: www.elearn.isra.edu.jo Course Classification: Department Compulsory (CIS) Time Division: 3 Lectures Semester &Year: Second 2011/2012 Course Description (3 credit hours, Prerequisite: 601322/ Data Warehouses) Introduction to data mining, Input Concepts, Knowledge Representation, Decision Tables, Decision Trees, Classification Rules, Association Rules, Data Mining Algorithms and Implementations in Java. Course Intended Outcomes At the end of the course, students are expected to learn: Data Mining and Machine Learning Concepts and uses The different types of Data Mining techniques How to decide which technique to use with different problems How to implement Data mining methods in the Java Language Course Outline Week 1 2 3 ROOM: 4142 SUN/9:00-9:50 Introduction to Data Mining & Course Outline Data mining and machine learning (Ch 1- Introduction) Generalization as Search (Ch1) Attributes (Ch 2) ROOM: 4142 TUE/9:00-9:50 Data Warehousing – Review1 Simple Examples (Ch 1) Concepts (Ch2 - Input) Preparing the Input (Ch 2) 4 5 6 Decision Trees (Ch 3) Rules with Exceptions (Ch 3) Rules Involving Relations (Ch 3) Review for First Exam First Exam (Th 24/11/2011) 7 8 9 Classification Rules (Ch 3) Instance-based Representation (Ch 3) Statistical Modeling (Ch 4) Clusters (Ch 3) Constructing Decision Trees (Ch 4) 10 Mining Association Rules (Ch 4) Linear Models (Ch 4) 11 Review for Second Exam Second Exam (Tu 27/12/2011) 12 Training & Testing Predicting performance Cross-validation (Ch5 - Credibility / Evaluating what's been learned) Other estimates Comparing data mining Schemes Predicting Probabilities (Ch 5) 13 Decision trees Classification rules (Ch 6 - Support vector machines Instance-based Learning (Ch 6) ROOM: 4142 THU/ 9:00-9:50 Data Warehousing – Review2 Fielded Applications (Ch 1) Instances (Ch 2) Decision tables ( Ch 3 – Output / Knowledge Representation ) Association Rules (Ch 3) Trees for Numeric Prediction (Ch 3) Return and Discussion of First Exam Results Inferring rudimentary (Ch 4 – Algorithms) Constructing Rules (Ch 4) Instance-based Learning (Ch 4) Return and Discussion of Second Exam Results Counting the cost Evaluating numeric prediction The minimum description length principle (Ch 5) Numeric prediction Clustering (Ch 6) Isra University 2 Faculty Information Technology Department of Computer Science Course Plan ________________________________________________________________________________________________ Implementation) Exam Review Third Exam 14 Exam Review ( TBA) Final Exams 15 Textbook Data Mining: Practical machine learning tools and techniques with Java implementation. Ian Witten, Eibe Frank. Morgan Kaufmann, 3rd Ed. Suggested references 1. 2. 3. Data Mining, Adriaans, Zantige, Addison-Wesley, 1997. Discovering data mining: From concepts to implementation, Cabena, Hadjinian, Prentice Hall, 1998. Machine learning, Mitchell, McGraw Hill, 1997. Marking First Exam Second Exam Activity Final Exam 25 marks 25 marks 10 marks 40 marks Regulations 1. 2. 3. 4. 5. There will be three term exams given during this semester. The best two out of three will be considered for the First and Second Exam. This means: there will be NO makeup exams! Missing one of the two left exams means a ZERO grade will be given for that exam. There are no makeup for quizzes Attendance is mandatory and University regulations will be enforced. All Cheating incidents will be reported to the chair. The following activities are considered cheating: a. Turning in assignment that includes parts of someone else's work. b. Turning in someone else’s assignment as your own. c. Giving assignment to someone else to turn in as their own. d. Copying answers in a test or quiz. e. Taking a test or quiz for someone else. f. Having someone else take a test or quiz for you. See Student handbook for other regulations. Assignments and/or Projects Assignments / Description Due Date Marking Quizzes In each major section the students will be given assignments for practicing and developing a good concept of the topic. Assignments’ deadlines and method of delivery will be specified by instructors throughout the course. Emailing Guidelines: 1. 2. 3. 4. All homework, assignments, projects, etc., are sent by email to the email address shown below ( under Instructor’s Information). Be sure to send them before the due date. Fill in the subject field of the email using the following format: CIS201_Family-Name_First-Name_Subject , where: a) CIS201 is abbreviation for the course. Other courses should have similar abbreviations b) Family-Name and First-Name are replaced by your family name and your first name. c) Subject is replaced by the title of the assignment, project, etc. You may also use the email to ask questions about the course. In this case, just type the world “question” in the place of _Subject as described in 3-c above. Isra University 3 Faculty Information Technology Department of Computer Science Course Plan ________________________________________________________________________________________________ Required Tools/Software Java SE Development Kit (JDK 6 or higher) [ http://java.sun.com/javase ] TextPad 5.1 [ http://www.textpad.com ] Eclipse IDE for Java Developers [ http://www.eclipse.org/downloads ] Instructor's Information Lecture Room : 4142 Lab : 4319 Instructor's Name: Dr. Mohammad Ali H. Eljinini Email: [email protected] Section: 1 Office Hours: Time:09:00-10:50 (SUN) Time:09:00-10:50 (TUE/THR) Office No.: 4106 Sun [11:00-12:00] Mon [09:00-10:00, 11:00-12:00] Tue [1:00-2:00] Wed[ 10:00-11:00,12:00-1:00] Other office hours are available by appointment Important: The content of this syllabus may not be changed during the current semester Instructor Council Chair