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Created: 11/05/10 @ 19:04:30 | Last updated: 11/05/10 @ 19:04:32
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License: Creative Commons Attribution-Share Alike 3.0 Unported License
Scientific value Using gene-expression patterns associated with DLBCL and FL to predict the lymphoma type of an unknown sample. Using SVM (Support Vector Machine) to classify data, and predicting the tumor types of unknown examples. Steps Querying training data from experiments stored in caArray. Preprocessing, or normalize the microarray data. Adding training and testing data into SVM service to get classification result.
Rating: 5.0 / 5 (1 rating) | Versions: 7 | Reviews: 0 | Comments: 0 | Citations: 3 Viewed: 585 times | Downloaded: 228 times Tags (11): |
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Created: 24/05/10 @ 22:34:31 | Last updated: 24/05/10 @ 22:34:32
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License: Creative Commons Attribution-Share Alike 3.0 Unported License
Support-Vector-Machine based data classificationSupport-Vector-Machine based data classification using genePattern SVM service, the input should be in genePattern STATML format.
Rating: 0.0 / 5 (0 ratings) | Versions: 2 | Reviews: 0 | Comments: 0 | Citations: 0 Viewed: 99 times | Downloaded: 46 times Tags (5): |
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