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--- |
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library_name: sklearn |
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license: mit |
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tags: |
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- sklearn |
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- skops |
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- tabular-classification |
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model_format: pickle |
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model_file: model_fold_2.pkl |
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widget: |
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- structuredData: |
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x0: |
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- 0.0 |
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- 0.9278350515463918 |
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- 0.0 |
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x1: |
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- 59199.0 |
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- 7.0 |
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- 744.0 |
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x2: |
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- 59047.0 |
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- 0.0 |
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- 790.0 |
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x3: |
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- 0.0 |
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- 28.0 |
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- 8.0 |
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x4: |
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- 0.0 |
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- 1.0 |
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- 1.0 |
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x5: |
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- 1.0 |
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- 1.0 |
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- 1.0 |
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--- |
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# Model description |
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<details> |
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<summary> Click to expand </summary> |
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This is a random forest classifier capable of predicting whether a given pair of transcriptscome from the same gene or not. It is trained on a dataset derived from ensembl transcripts, and is being evaluated on transcripts from the same sources, and others such as FlyBase |
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</details> |
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# How to Get Started with the Model |
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[More Information Needed] |
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# Model Card Authors |
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<details> |
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<summary> Click to expand </summary> |
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Andrew Green (afg1) |
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</details> |
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# Model Card Contact |
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You can contact the model card authors through following channels: |
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[More Information Needed] |
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# Citation |
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Below you can find information related to citation. |
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**BibTeX:** |
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``` |
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[More Information Needed] |
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``` |
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# Intended uses & limitations |
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<details> |
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<summary> Click to expand </summary> |
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This model is experimental, and is undergoing further testing. |
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</details> |
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# Five-fold cross validation |
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We test the model on a random subset of the transcript pairs processed from all our coordinate data. These metrics represent the performance on the binary classification task of 'do these two transcripts come from the same gene' |
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| fold | balanced_acc | F1 | auc | ap | |
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|--------|----------------|----------|----------|----------| |
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| 0 | 0.970089 | 0.989711 | 0.995063 | 0.998216 | |
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| 1 | 0.968053 | 0.98935 | 0.994941 | 0.998181 | |
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| 2 | 0.970278 | 0.989625 | 0.995177 | 0.998239 | |
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| 3 | 0.968382 | 0.989364 | 0.994861 | 0.998184 | |
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| 4 | 0.968858 | 0.989405 | 0.994907 | 0.997969 | |
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