assignments:assignment3
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assignments:assignment3 [2015/10/02 10:04] asa |
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| ========= Assignment 3: Support Vector Machines ============ | ========= Assignment 3: Support Vector Machines ============ | ||
| - | Due: October 20th at 6pm | + | Due: October 16th at 11pm |
| ===== Part 1: SVM with no bias term ===== | ===== Part 1: SVM with no bias term ===== | ||
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| of distinguishing a particular class of proteins from a selection of | of distinguishing a particular class of proteins from a selection of | ||
| examples sampled from the rest of the SCOP database | examples sampled from the rest of the SCOP database | ||
| - | using features derived from their sequence (note that a protein is an arbitrary length sequence over the alphabet of the 20 amino acids). | + | using features derived from their sequence (a protein is a chain of amino acids, so as computer scientists, we can consider it as a sequence over the alphabet of the 20 amino acids). |
| - | I chose to represent the proteins in | + | I chose to represent the proteins in terms of their motif composition. A sequence motif is a |
| - | terms of their motif composition. A sequence motif is a | + | |
| pattern of amino acids that is conserved in evolution. | pattern of amino acids that is conserved in evolution. | ||
| Motifs are usually associated with regions of the protein that are | Motifs are usually associated with regions of the protein that are | ||
| Line 41: | Line 40: | ||
| so the data is very sparse. | so the data is very sparse. | ||
| Therefore, only the non-zero elements of the data are represented. | Therefore, only the non-zero elements of the data are represented. | ||
| - | Each line in the file describes a single example and has the format: | + | Each line in the file describes a single example. Here's an example from the file: |
| <code> | <code> | ||
| Line 95: | Line 94: | ||
| ===== Submission ===== | ===== Submission ===== | ||
| - | Submit your report via Canvas. Python code can be displayed in your report if it is succinct (not more than a page or two at the most) or submitted separately. The latex sample document shows how to display Python code in a latex document. Code needs to be there so we can make sure that you implemented the algorithms and data analysis methodology correctly. Canvas allows you to submit multiple files for an assignment, so DO NOT submit an archive file (tar, zip, etc). | + | Submit the pdf of your report via Canvas. Python code can be displayed in your report if it is succinct (not more than a page or two at the most) or submitted separately. The latex sample document shows how to display Python code in a latex document. Code needs to be there so we can make sure that you implemented the algorithms and data analysis methodology correctly. Canvas allows you to submit multiple files for an assignment, so DO NOT submit an archive file (tar, zip, etc). Canvas will only allow you to submit pdfs (.pdf extension) or python code (.py extension) |
| ===== Grading ===== | ===== Grading ===== | ||
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| Grading sheet for assignment 2 | Grading sheet for assignment 2 | ||
| - | Part 1: 45 points. | + | Part 1: 40 points. |
| (10 points): Primal SVM formulation is correct | (10 points): Primal SVM formulation is correct | ||
| (10 points): Lagrangian found correctly | (10 points): Lagrangian found correctly | ||
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| ( 5 points): Discussion of the implication of the form of the dual for SMO-like algorithms | ( 5 points): Discussion of the implication of the form of the dual for SMO-like algorithms | ||
| - | Part 2: 15 points. | + | Part 2: 10 points. |
| Part 3: 40 points. | Part 3: 40 points. | ||
assignments/assignment3.txt · Last modified: 2016/09/20 09:34 by asa
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