Course - Machine Learning and Case-Based Reasoning - TDT4173
TDT4173 - Machine Learning and Case-Based Reasoning
About
Examination arrangement
Examination arrangement: Portfolio assessment
Grade: Letters
Evaluation | Weighting | Duration | Grade deviation | Examination aids |
---|---|---|---|---|
Arbeider | 20/100 | |||
Skriftlig eksamen | 80/100 | 4 timer |
Course content
The course gives an introduction to the principles and methods for automatic learning in computer systems. Classical syntax-based learning methods as well as more knowledge-intensive methods are described. Main empahsis is on symbolic methods, where explicit concepts and relationships are learned. Statistical methods and reinforcement learning is also included. The strengths and weaknesses of various methods are compared.
Learning methods in case-based reasoning and the integration of learning and problem solving is given particular treatment. Numerical and cognitive models for similarity asessment will be discussed, together with different learning system architectures. Methods that combine case-based and generalisation-based inferences will be discussed as well.
Learning outcome
The aim of the course is to introduce principles of machine learning methods in general and case-based methods in particular, to students with a basic knowledge of AI methods.
Learning methods and activities
Lectures, colloquia, self study, exercises. Portfolio assessment is the basis for the grade in the course. The portfolio includes a final written exam (80%) and exercises (20%). The results for the parts are given in %-scores, while the entire portfolio is assigned a letter grade. If there is a re-sit examination, the examination form may be changed from written to oral.
Recommended previous knowledge
TDT4136 Introduction to Artificial Intelligence, TDT4171 Artificial Intelligence Methods or similar.
Course materials
Text book: Tom Mitchell: Machine learning, McGraw Hill, 1997. Scientific papers: To be determined at course start.
Credit reductions
Course code | Reduction | From | To |
---|---|---|---|
IT3704 | 7.5 | ||
MNFIT374 | 7.5 | ||
MNFIT374 | 7.5 |
No
Version: 1
Credits:
7.5 SP
Study level: Second degree level
Term no.: 1
Teaching semester: AUTUMN 2014
Language of instruction: English
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- Industrial Economics
- Information Security
- Informatics
- Psychology
- Statistics
- Technological subjects
Department with academic responsibility
Department of Computer Science
Examination
Examination arrangement: Portfolio assessment
- Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
- Autumn ORD Arbeider 20/100
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Room Building Number of candidates - Autumn ORD Skriftlig eksamen 80/100 2014-12-13 09:00
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Room Building Number of candidates - Summer KONT Arbeider 20/100
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Room Building Number of candidates - Summer KONT Oral examination 80/100 2015-08-03
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Room Building Number of candidates
- * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
For more information regarding registration for examination and examination procedures, see "Innsida - Exams"