| Line 19: | Line 19: | ||
---- | ---- | ||
| − | == | + | ==All versus All Classification== |
| − | + | ||
| − | + | If you thought this course could not been more fun, then you are wrong. With this competition, everything becomes more interesting. We are talking about a competition among the best students in the world in one of the coolest field of study, pattern recognition! Which classifier will make a better prediction for this data, SVM, Bayes, KNN .. ? How much should I fit my classifier with the training data? Hopefully we can solve this questions by the end of the competition. | |
| − | + | For this part of the homework, all you have to do is [https://www.projectrhea.org/rhea/index.php/Special:DropBox?forUser=drugeles&assn=true submit here] a text file with the following schema: | |
<p> | <p> | ||
| − | + | Joe Blo<br /> | |
| − | <br /> | + | 77%<br /> |
1<br /> | 1<br /> | ||
0<br /> | 0<br /> | ||
| Line 42: | Line 41: | ||
1<br /> | 1<br /> | ||
<br /> | <br /> | ||
| − | + | ||
| − | + | ||
| − | + | The first row is your nickname.<br /> | |
| + | The second row is your predicted results computed with the training set.<br /> | ||
| + | All the other rows are your prediction from the test set. Please classify keeping the order given in the test set.<br /> | ||
| + | <br /> | ||
| + | |||
| + | Please submit <strong>before May 2012.</strong> | ||
---- | ---- | ||
==Result Summary== | ==Result Summary== | ||
| + | This results will be computed from the submissions in drugeles dropbox. Refer to All versus All Classification section. | ||
{| | {| | ||
! style="background: rgb(238, 238, 238) none repeat scroll 0% 0%; -moz-background-clip: -moz-initial; -moz-background-origin: -moz-initial; -moz-background-inline-policy: -moz-initial;" colspan="4" |column labels go here | ! style="background: rgb(238, 238, 238) none repeat scroll 0% 0%; -moz-background-clip: -moz-initial; -moz-background-origin: -moz-initial; -moz-background-inline-policy: -moz-initial;" colspan="4" |column labels go here | ||
|- | |- | ||
| − | |Nickname (add link to method summary) | + | |Position |
| + | |Nickname (add link to method summary or report) | ||
|Confusion Matrix | |Confusion Matrix | ||
|Overall Accuracy | |Overall Accuracy | ||
|Predicted Accuracy | |Predicted Accuracy | ||
|- | |- | ||
| + | | 5 | ||
| Joe Blo (method summary) | | Joe Blo (method summary) | ||
|<math> | |<math> | ||
Revision as of 08:02, 17 April 2012
Contents
Third Homework, ECE662 Spring 2012
Email code to your instructor before 11:59pm, Friday April 27, 2012. Report due before 11:59pm, Monday April 30, in your instructor's Rhea dropbox. Make sure to drop it in the correct homework folder!!!!. It is the one at the very bottom of the page.
Automatic Pattern Recognition Contest!
An anonymous company has agreed to share real data with us, so we are going to have a little contest using this data! The data comes from a five-class classification problem using 13 features. We are looking for the student who will design the most accurate classifier using this data.
The training data consists of 550 data points (i.e. 550 points in a 13 dimensional space) along with the correct label for each point. Use this data, along with any method of your choice, to design what you think is an accurate classifier. When you are done designing your classifier, email your source code to your instructor, and you will receive the testing data. Then without changing your code, test your classifier on the testing data and note its accuracy. Summarize your method and results in a report.
If you feel like sharing your results and methods publicly, feel free to post a copy of your work below, but only after the deadline for the homework has past.
The discussion page for this homework is here.
All versus All Classification
If you thought this course could not been more fun, then you are wrong. With this competition, everything becomes more interesting. We are talking about a competition among the best students in the world in one of the coolest field of study, pattern recognition! Which classifier will make a better prediction for this data, SVM, Bayes, KNN .. ? How much should I fit my classifier with the training data? Hopefully we can solve this questions by the end of the competition.
For this part of the homework, all you have to do is submit here a text file with the following schema:
Joe Blo
77%
1
0
1
2
3
4
2
3
1
2
0
2
1
The first row is your nickname.
The second row is your predicted results computed with the training set.
All the other rows are your prediction from the test set. Please classify keeping the order given in the test set.
Please submit before May 2012.
Result Summary
This results will be computed from the submissions in drugeles dropbox. Refer to All versus All Classification section.
| column labels go here | ||||
|---|---|---|---|---|
| Position | Nickname (add link to method summary or report) | Confusion Matrix | Overall Accuracy | Predicted Accuracy |
| 5 | Joe Blo (method summary) | $ \left( \begin{array}{cccccc} &\mathbf{0}&\mathbf{1}&\mathbf{2}&\mathbf{3}&\mathbf{4}\\ \mathbf{0}& x& x& x& x& x \\ \mathbf{1}& x& x& x& x&x \\ \mathbf{2}& x& x& x& x&x \\ \mathbf{3}& x& x& x& x& x\\ \mathbf{4}& x& x& x& x&x \\ \end{array} \right) $ | 75% | 77% |
Back to ECE 662 Spring 2012
