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README.md

@@ -37,137 +37,26 @@ widget:
 
 # Model description
 
-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
-
-## Intended uses & limitations
-
-This model is experimental, and is undergoing further testing.
-
-## Training Procedure
-
-[More Information Needed]
-
-### Hyperparameters
-
 <details>
 <summary> Click to expand </summary>
 
-| Hyperparameter           | Value   |
-|--------------------------|---------|
-| bootstrap                | True    |
-| ccp_alpha                | 0.0     |
-| class_weight             |         |
-| criterion                | gini    |
-| max_depth                |         |
-| max_features             | sqrt    |
-| max_leaf_nodes           |         |
-| max_samples              |         |
-| min_impurity_decrease    | 0.0     |
-| min_samples_leaf         | 1       |
-| min_samples_split        | 2       |
-| min_weight_fraction_leaf | 0.0     |
-| monotonic_cst            |         |
-| n_estimators             | 100     |
-| n_jobs                   | -1      |
-| oob_score                | True    |
-| random_state             |         |
-| verbose                  | 0       |
-| warm_start               | False   |
+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
 
 </details>
 
-### Model Plot
-
-<style>#sk-container-id-1 {/* Definition of color scheme common for light and dark mode */--sklearn-color-text: black;--sklearn-color-line: gray;/* Definition of color scheme for unfitted estimators */--sklearn-color-unfitted-level-0: #fff5e6;--sklearn-color-unfitted-level-1: #f6e4d2;--sklearn-color-unfitted-level-2: #ffe0b3;--sklearn-color-unfitted-level-3: chocolate;/* Definition of color scheme for fitted estimators */--sklearn-color-fitted-level-0: #f0f8ff;--sklearn-color-fitted-level-1: #d4ebff;--sklearn-color-fitted-level-2: #b3dbfd;--sklearn-color-fitted-level-3: cornflowerblue;/* Specific color for light theme */--sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));--sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));--sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));--sklearn-color-icon: #696969;@media (prefers-color-scheme: dark) {/* Redefinition of color scheme for dark theme */--sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));--sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));--sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));--sklearn-color-icon: #878787;}
-}#sk-container-id-1 {color: var(--sklearn-color-text);
-}#sk-container-id-1 pre {padding: 0;
-}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;
-}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed var(--sklearn-color-line);margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: var(--sklearn-color-background);
-}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }`but bootstrap.min.css set `[hidden] { display: none !important; }`so we also need the `!important` here to be able to override thedefault hidden behavior on the sphinx rendered scikit-learn.org.See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;
-}#sk-container-id-1 div.sk-text-repr-fallback {display: none;
-}div.sk-parallel-item,
-div.sk-serial,
-div.sk-item {/* draw centered vertical line to link estimators */background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));background-size: 2px 100%;background-repeat: no-repeat;background-position: center center;
-}/* Parallel-specific style estimator block */#sk-container-id-1 div.sk-parallel-item::after {content: "";width: 100%;border-bottom: 2px solid var(--sklearn-color-text-on-default-background);flex-grow: 1;
-}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: var(--sklearn-color-background);position: relative;
-}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;
-}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;
-}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;
-}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;
-}/* Serial-specific style estimator block */#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: var(--sklearn-color-background);padding-right: 1em;padding-left: 1em;
-}/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is
-clickable and can be expanded/collapsed.
-- Pipeline and ColumnTransformer use this feature and define the default style
-- Estimators will overwrite some part of the style using the `sk-estimator` class
-*//* Pipeline and ColumnTransformer style (default) */#sk-container-id-1 div.sk-toggleable {/* Default theme specific background. It is overwritten whether we have aspecific estimator or a Pipeline/ColumnTransformer */background-color: var(--sklearn-color-background);
-}/* Toggleable label */
-#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.5em;box-sizing: border-box;text-align: center;
-}#sk-container-id-1 label.sk-toggleable__label-arrow:before {/* Arrow on the left of the label */content: "▸";float: left;margin-right: 0.25em;color: var(--sklearn-color-icon);
-}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: var(--sklearn-color-text);
-}/* Toggleable content - dropdown */#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;/* unfitted */background-color: var(--sklearn-color-unfitted-level-0);
-}#sk-container-id-1 div.sk-toggleable__content.fitted {/* fitted */background-color: var(--sklearn-color-fitted-level-0);
-}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;border-radius: 0.25em;color: var(--sklearn-color-text);/* unfitted */background-color: var(--sklearn-color-unfitted-level-0);
-}#sk-container-id-1 div.sk-toggleable__content.fitted pre {/* unfitted */background-color: var(--sklearn-color-fitted-level-0);
-}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {/* Expand drop-down */max-height: 200px;max-width: 100%;overflow: auto;
-}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: "▾";
-}/* Pipeline/ColumnTransformer-specific style */#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {color: var(--sklearn-color-text);background-color: var(--sklearn-color-unfitted-level-2);
-}#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: var(--sklearn-color-fitted-level-2);
-}/* Estimator-specific style *//* Colorize estimator box */
-#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {/* unfitted */background-color: var(--sklearn-color-unfitted-level-2);
-}#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {/* fitted */background-color: var(--sklearn-color-fitted-level-2);
-}#sk-container-id-1 div.sk-label label.sk-toggleable__label,
-#sk-container-id-1 div.sk-label label {/* The background is the default theme color */color: var(--sklearn-color-text-on-default-background);
-}/* On hover, darken the color of the background */
-#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {color: var(--sklearn-color-text);background-color: var(--sklearn-color-unfitted-level-2);
-}/* Label box, darken color on hover, fitted */
-#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {color: var(--sklearn-color-text);background-color: var(--sklearn-color-fitted-level-2);
-}/* Estimator label */#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;
-}#sk-container-id-1 div.sk-label-container {text-align: center;
-}/* Estimator-specific */
-#sk-container-id-1 div.sk-estimator {font-family: monospace;border: 1px dotted var(--sklearn-color-border-box);border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;/* unfitted */background-color: var(--sklearn-color-unfitted-level-0);
-}#sk-container-id-1 div.sk-estimator.fitted {/* fitted */background-color: var(--sklearn-color-fitted-level-0);
-}/* on hover */
-#sk-container-id-1 div.sk-estimator:hover {/* unfitted */background-color: var(--sklearn-color-unfitted-level-2);
-}#sk-container-id-1 div.sk-estimator.fitted:hover {/* fitted */background-color: var(--sklearn-color-fitted-level-2);
-}/* Specification for estimator info (e.g. "i" and "?") *//* Common style for "i" and "?" */.sk-estimator-doc-link,
-a:link.sk-estimator-doc-link,
-a:visited.sk-estimator-doc-link {float: right;font-size: smaller;line-height: 1em;font-family: monospace;background-color: var(--sklearn-color-background);border-radius: 1em;height: 1em;width: 1em;text-decoration: none !important;margin-left: 1ex;/* unfitted */border: var(--sklearn-color-unfitted-level-1) 1pt solid;color: var(--sklearn-color-unfitted-level-1);
-}.sk-estimator-doc-link.fitted,
-a:link.sk-estimator-doc-link.fitted,
-a:visited.sk-estimator-doc-link.fitted {/* fitted */border: var(--sklearn-color-fitted-level-1) 1pt solid;color: var(--sklearn-color-fitted-level-1);
-}/* On hover */
-div.sk-estimator:hover .sk-estimator-doc-link:hover,
-.sk-estimator-doc-link:hover,
-div.sk-label-container:hover .sk-estimator-doc-link:hover,
-.sk-estimator-doc-link:hover {/* unfitted */background-color: var(--sklearn-color-unfitted-level-3);color: var(--sklearn-color-background);text-decoration: none;
-}div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,
-.sk-estimator-doc-link.fitted:hover,
-div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,
-.sk-estimator-doc-link.fitted:hover {/* fitted */background-color: var(--sklearn-color-fitted-level-3);color: var(--sklearn-color-background);text-decoration: none;
-}/* Span, style for the box shown on hovering the info icon */
-.sk-estimator-doc-link span {display: none;z-index: 9999;position: relative;font-weight: normal;right: .2ex;padding: .5ex;margin: .5ex;width: min-content;min-width: 20ex;max-width: 50ex;color: var(--sklearn-color-text);box-shadow: 2pt 2pt 4pt #999;/* unfitted */background: var(--sklearn-color-unfitted-level-0);border: .5pt solid var(--sklearn-color-unfitted-level-3);
-}.sk-estimator-doc-link.fitted span {/* fitted */background: var(--sklearn-color-fitted-level-0);border: var(--sklearn-color-fitted-level-3);
-}.sk-estimator-doc-link:hover span {display: block;
-}/* "?"-specific style due to the `<a>` HTML tag */#sk-container-id-1 a.estimator_doc_link {float: right;font-size: 1rem;line-height: 1em;font-family: monospace;background-color: var(--sklearn-color-background);border-radius: 1rem;height: 1rem;width: 1rem;text-decoration: none;/* unfitted */color: var(--sklearn-color-unfitted-level-1);border: var(--sklearn-color-unfitted-level-1) 1pt solid;
-}#sk-container-id-1 a.estimator_doc_link.fitted {/* fitted */border: var(--sklearn-color-fitted-level-1) 1pt solid;color: var(--sklearn-color-fitted-level-1);
-}/* On hover */
-#sk-container-id-1 a.estimator_doc_link:hover {/* unfitted */background-color: var(--sklearn-color-unfitted-level-3);color: var(--sklearn-color-background);text-decoration: none;
-}#sk-container-id-1 a.estimator_doc_link.fitted:hover {/* fitted */background-color: var(--sklearn-color-fitted-level-3);
-}
-</style><div id="sk-container-id-1" class="sk-top-container" style="overflow: auto;"><div class="sk-text-repr-fallback"><pre>RandomForestClassifier(n_jobs=-1, oob_score=True)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class="sk-container" hidden><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-1" type="checkbox" checked><label for="sk-estimator-id-1" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;&nbsp;RandomForestClassifier<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.4/modules/generated/sklearn.ensemble.RandomForestClassifier.html">?<span>Documentation for RandomForestClassifier</span></a><span class="sk-estimator-doc-link fitted">i<span>Fitted</span></span></label><div class="sk-toggleable__content fitted"><pre>RandomForestClassifier(n_jobs=-1, oob_score=True)</pre></div> </div></div></div></div>
-
-## Evaluation Results
-
-[More Information Needed]
-
 # How to Get Started with the Model
 
 [More Information Needed]
 
 # Model Card Authors
 
+<details>
+<summary> Click to expand </summary>
+
 Andrew Green (afg1)
 
+</details>
+
 # Model Card Contact
 
 You can contact the model card authors through following channels:
@@ -184,16 +73,21 @@ Below you can find information related to citation.
 
 # Intended uses & limitations
 
+<details>
+<summary> Click to expand </summary>
+
 This model is experimental, and is undergoing further testing.
 
+</details>
+
 # Five-fold cross validation
 
 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'
 
-|   balanced_acc |       F1 |      auc |       ap |
-|----------------|----------|----------|----------|
-|       0.970089 | 0.989711 | 0.995063 | 0.998216 |
-|       0.968053 | 0.98935  | 0.994941 | 0.998181 |
-|       0.970278 | 0.989625 | 0.995177 | 0.998239 |
-|       0.968382 | 0.989364 | 0.994861 | 0.998184 |
-|       0.968858 | 0.989405 | 0.994907 | 0.997969 |
+|   fold |   balanced_acc |       F1 |      auc |       ap |
+|--------|----------------|----------|----------|----------|
+|      0 |       0.970089 | 0.989711 | 0.995063 | 0.998216 |
+|      1 |       0.968053 | 0.98935  | 0.994941 | 0.998181 |
+|      2 |       0.970278 | 0.989625 | 0.995177 | 0.998239 |
+|      3 |       0.968382 | 0.989364 | 0.994861 | 0.998184 |
+|      4 |       0.968858 | 0.989405 | 0.994907 | 0.997969 |