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Laboratory of Computer and Information Science / Neural Networks Research Centre CIS Lab Helsinki University of Technology

Helsinki University of Technology → Department of Computer Science and Engineering →
Laboratory of Computer and Information Science → Teaching →
T-61.3050 Machine Learning: Basic Principles → 2007 → Grading principles

Grading principles 2007 - T-61.3050

To pass the course both the examination and the term project must be passed.

The 2007 examination, if passed, is graded on a scale from 0 to 1 (grade may be fractional). The smallest passed grade is 0. The grade is a monotonic, but not necessarily linear, function of total points from the examination. We have used E=(PT-15)/15, where PT are the total points from the examination (smallest passed total points being PT=15, highest PT=30) - the exact formula may however change depending, for example, on the difficulty of the examination. Denote the examination grade by E.

The 2007 term project, if passed, is graded on a scale from 0 to 1 (grade may be fractional). The smallest passed grade is 0. Denote the term project grade by T.

The 2007 problem sessions are graded on a scale from 0 to 1 (grade may be fractional). The grade of 0 corresponds to no points from the problem sessions. Denote the problem session grade by P.

The course grade is then given by min(5,floor(1+4*E+2*T+P)).

Guidelines for grading of the answers

Some general guidelines for grading of the examination and term project answers are given below (which are quite similar to the grading criteria of the Finnish high school final examination, "reaalikoe"). Notice that in addition to having a correct factual content a good answer should be, among other things, understandable for the examiner.

Signs of a strong answer:

Signs of a weak answer:

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