Prediction details
Each row in the following table shows the accuracy of predictions by an algorithm for individual cells in the data set. "Overall best CC" indicates the performance of the current best algorithm for that cell.
1. V1 Natural Vision Movies - List cells - All predictions - My predictions - Download data set - Submit prediction!| Algorithm: | MID v5.0 |
| User: | jakem |
| Notes: | Used Maximally Informative Dimensions to simplify the stimulus using most informative filter, and predicted using line of best fit. Some used 2d MID, some only 1d, cells used varying methods of fitting to the curve based on how well it did in preliminary tests.
Ran preliminary tests by splitting known data into 7/8 and 1/8, running 7/8 through MID, and attempting to predict the last 1/8, then comparing. Hoping to get better results from this submission because it used all the stimulus data in MID. Had a few unique issues with the fact that many of the frames in sequence in these movies are constant. Led to some interesting filters, but in some cases, better results that previous predictions. Had issues with NaN-values in my first submission, but I replaced them with avg firing rate. Also ran into alignment issues. Which now should be solved.... maybe... |
| Eval'd on: | 2010-07-21 12:37:01 (Prediction evaluated successfully) |
| Cell ID | My CC | Overall Best CC | |
| r0206B | 0.333 | 0.743 | |
| r0208D | 0.416 | 0.549 | |
| r0210A | 0.292 | 0.609 | |
| r0211A | 0.199 | 0.400 | |
| r0212B | 0.474 | 0.556 | |
| r0217B | 0.360 | 0.337 | |
| r0219B | 0.051 | 0.487 | |
| r0220A | -0.004 | 0.314 | |
| r0221A | 0.304 | 0.708 | |
| r0222A | 0.621 | 0.731 | |
| r0223A | 0.352 | 0.631 | |
| r0225C | -0.021 | 0.636 |
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