assignments:assignment5
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assignments:assignment5 [2016/10/17 19:20] asa |
assignments:assignment5 [2016/10/17 19:25] asa [Submission] |
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| ===== Submission ===== | ===== Submission ===== | ||
| - | Submit your report via Canvas. Python code can be displayed in your report if it is short, and helps understand what you have done. The sample LaTex document provided in assignment 1 shows how to display Python code. Submit the Python code that was used to generate the results as a file called ''assignment3.py'' (you can split the code into several .py files; Canvas allows you to submit multiple files). Typing | + | Submit your report via Canvas. Python code can be displayed in your report if it is short, and helps understand what you have done. The sample LaTex document provided in assignment 1 shows how to display Python code. Submit the Python code that was used to generate the results as a file called ''assignment5.py'' (you can split the code into several .py files; Canvas allows you to submit multiple files). Typing |
| <code> | <code> | ||
| - | $ python assignment4.py | + | $ python assignment5.py |
| </code> | </code> | ||
| should generate all the tables/plots used in your report. | should generate all the tables/plots used in your report. | ||
| Line 59: | Line 59: | ||
| <code> | <code> | ||
| - | Grading sheet for assignment 4 | + | Grading sheet for assignment 5 |
| - | Part 1: 40 points. | + | Part 1: 15 points. |
| - | ( 5 points): Primal SVM formulation is correct | + | |
| - | (10 points): Lagrangian found correctly | + | |
| - | (10 points): Derivation of saddle point equations | + | |
| - | (15 points): Derivation of the dual | + | |
| - | + | ||
| - | Part 2: 15 points. | + | |
| - | + | ||
| - | Part 2: 15 points. | + | |
| - | + | ||
| - | Part 3: 30 points. | + | |
| - | (15 points): Accuracy as a function of parameters and discussion of the results | + | |
| - | (10 points): Comparison of normalized and non-normalized kernels and correct model selection | + | |
| - | ( 5 points): Visualization of the kernel matrix and observations made about it | + | |
| + | Part 2: 85 points. | ||
| + | (25 points): Exploration of a network with a single hidden layer | ||
| + | (25 points): Exploration of a network with two hidden layers | ||
| + | (15 points): How to add weight decay | ||
| + | (15 points): Linear activation function | ||
| + | ( 5 points): Fixing the code so it handles the bias term correctly | ||
| </code> | </code> | ||
assignments/assignment5.txt · Last modified: 2016/10/18 09:18 by asa
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