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Browse files- README.md +162 -0
- config.json +1 -0
- model.pkl +3 -0
- namegender.csv +0 -0
README.md
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# Model description
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This is a Decision tree model trained name based on gender probability dataset
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## Intended uses & limitations
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This model is made for educational purposes and is not ready to be used in production.
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## Training Procedure
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[More Information Needed]
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### Hyperparameters
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<details>
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<summary> Click to expand </summary>
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| Hyperparameter | Value |
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| :----------------------: | :---: |
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| ccp_alpha | 0.0 |
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| class_weight | None |
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| criterion | gini |
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| max_depth | 6 |
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| max_features | None |
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| max_leaf_nodes | None |
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| min_impurity_decrease | 0.0 |
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| min_samples_leaf | 1 |
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| min_samples_split | 2 |
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| min_weight_fraction_leaf | 0.0 |
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| monotonic_cst | None |
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| random_state | None |
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| splitter | best |
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</details>
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### Model Plot
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<style>#sk-container-id-21 {/* Definition of color scheme common for light and dark mode */--sklearn-color-text: #000;--sklearn-color-text-muted: #666;--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;}
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}#sk-container-id-21 {color: var(--sklearn-color-text);
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}#sk-container-id-21 pre {padding: 0;
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}#sk-container-id-21 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;
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}#sk-container-id-21 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);
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}#sk-container-id-21 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;
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}#sk-container-id-21 div.sk-text-repr-fallback {display: none;
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}div.sk-parallel-item,
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div.sk-serial,
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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;
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}/* Parallel-specific style estimator block */#sk-container-id-21 div.sk-parallel-item::after {content: "";width: 100%;border-bottom: 2px solid var(--sklearn-color-text-on-default-background);flex-grow: 1;
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}#sk-container-id-21 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: var(--sklearn-color-background);position: relative;
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}#sk-container-id-21 div.sk-parallel-item {display: flex;flex-direction: column;
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}#sk-container-id-21 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;
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}#sk-container-id-21 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;
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}#sk-container-id-21 div.sk-parallel-item:only-child::after {width: 0;
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}/* Serial-specific style estimator block */#sk-container-id-21 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: var(--sklearn-color-background);padding-right: 1em;padding-left: 1em;
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}/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is
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clickable and can be expanded/collapsed.
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- Pipeline and ColumnTransformer use this feature and define the default style
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- Estimators will overwrite some part of the style using the `sk-estimator` class
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*//* Pipeline and ColumnTransformer style (default) */#sk-container-id-21 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);
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}/* Toggleable label */
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#sk-container-id-21 label.sk-toggleable__label {cursor: pointer;display: flex;width: 100%;margin-bottom: 0;padding: 0.5em;box-sizing: border-box;text-align: center;align-items: start;justify-content: space-between;gap: 0.5em;
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}#sk-container-id-21 label.sk-toggleable__label .caption {font-size: 0.6rem;font-weight: lighter;color: var(--sklearn-color-text-muted);
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}#sk-container-id-21 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);
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}#sk-container-id-21 label.sk-toggleable__label-arrow:hover:before {color: var(--sklearn-color-text);
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}/* Toggleable content - dropdown */#sk-container-id-21 div.sk-toggleable__content {display: none;text-align: left;/* unfitted */background-color: var(--sklearn-color-unfitted-level-0);
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}#sk-container-id-21 div.sk-toggleable__content.fitted {/* fitted */background-color: var(--sklearn-color-fitted-level-0);
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}#sk-container-id-21 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);
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}#sk-container-id-21 div.sk-toggleable__content.fitted pre {/* unfitted */background-color: var(--sklearn-color-fitted-level-0);
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}#sk-container-id-21 input.sk-toggleable__control:checked~div.sk-toggleable__content {/* Expand drop-down */display: block;width: 100%;overflow: visible;
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}#sk-container-id-21 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: "▾";
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}/* Pipeline/ColumnTransformer-specific style */#sk-container-id-21 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);
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}#sk-container-id-21 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: var(--sklearn-color-fitted-level-2);
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}/* Estimator-specific style *//* Colorize estimator box */
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#sk-container-id-21 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {/* unfitted */background-color: var(--sklearn-color-unfitted-level-2);
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}#sk-container-id-21 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {/* fitted */background-color: var(--sklearn-color-fitted-level-2);
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}#sk-container-id-21 div.sk-label label.sk-toggleable__label,
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#sk-container-id-21 div.sk-label label {/* The background is the default theme color */color: var(--sklearn-color-text-on-default-background);
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}/* On hover, darken the color of the background */
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#sk-container-id-21 div.sk-label:hover label.sk-toggleable__label {color: var(--sklearn-color-text);background-color: var(--sklearn-color-unfitted-level-2);
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}/* Label box, darken color on hover, fitted */
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#sk-container-id-21 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {color: var(--sklearn-color-text);background-color: var(--sklearn-color-fitted-level-2);
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}/* Estimator label */#sk-container-id-21 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;
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}#sk-container-id-21 div.sk-label-container {text-align: center;
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}/* Estimator-specific */
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#sk-container-id-21 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);
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}#sk-container-id-21 div.sk-estimator.fitted {/* fitted */background-color: var(--sklearn-color-fitted-level-0);
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}/* on hover */
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#sk-container-id-21 div.sk-estimator:hover {/* unfitted */background-color: var(--sklearn-color-unfitted-level-2);
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}#sk-container-id-21 div.sk-estimator.fitted:hover {/* fitted */background-color: var(--sklearn-color-fitted-level-2);
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}/* Specification for estimator info (e.g. "i" and "?") *//* Common style for "i" and "?" */.sk-estimator-doc-link,
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a:link.sk-estimator-doc-link,
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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: 0.5em;text-align: center;/* unfitted */border: var(--sklearn-color-unfitted-level-1) 1pt solid;color: var(--sklearn-color-unfitted-level-1);
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}.sk-estimator-doc-link.fitted,
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a:link.sk-estimator-doc-link.fitted,
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a:visited.sk-estimator-doc-link.fitted {/* fitted */border: var(--sklearn-color-fitted-level-1) 1pt solid;color: var(--sklearn-color-fitted-level-1);
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}/* On hover */
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div.sk-estimator:hover .sk-estimator-doc-link:hover,
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.sk-estimator-doc-link:hover,
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div.sk-label-container:hover .sk-estimator-doc-link:hover,
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.sk-estimator-doc-link:hover {/* unfitted */background-color: var(--sklearn-color-unfitted-level-3);color: var(--sklearn-color-background);text-decoration: none;
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}div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,
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.sk-estimator-doc-link.fitted:hover,
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div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,
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.sk-estimator-doc-link.fitted:hover {/* fitted */background-color: var(--sklearn-color-fitted-level-3);color: var(--sklearn-color-background);text-decoration: none;
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}/* Span, style for the box shown on hovering the info icon */
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.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);
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}.sk-estimator-doc-link.fitted span {/* fitted */background: var(--sklearn-color-fitted-level-0);border: var(--sklearn-color-fitted-level-3);
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}.sk-estimator-doc-link:hover span {display: block;
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}/* "?"-specific style due to the `<a>` HTML tag */#sk-container-id-21 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;
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}#sk-container-id-21 a.estimator_doc_link.fitted {/* fitted */border: var(--sklearn-color-fitted-level-1) 1pt solid;color: var(--sklearn-color-fitted-level-1);
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}/* On hover */
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#sk-container-id-21 a.estimator_doc_link:hover {/* unfitted */background-color: var(--sklearn-color-unfitted-level-3);color: var(--sklearn-color-background);text-decoration: none;
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}#sk-container-id-21 a.estimator_doc_link.fitted:hover {/* fitted */background-color: var(--sklearn-color-fitted-level-3);
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| 115 |
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}.estimator-table summary {padding: .5rem;font-family: monospace;cursor: pointer;
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}.estimator-table details[open] {padding-left: 0.1rem;padding-right: 0.1rem;padding-bottom: 0.3rem;
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| 117 |
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}.estimator-table .parameters-table {margin-left: auto !important;margin-right: auto !important;
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| 118 |
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}.estimator-table .parameters-table tr:nth-child(odd) {background-color: #fff;
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| 119 |
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}.estimator-table .parameters-table tr:nth-child(even) {background-color: #f6f6f6;
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}.estimator-table .parameters-table tr:hover {background-color: #e0e0e0;
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| 121 |
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}.estimator-table table td {border: 1px solid rgba(106, 105, 104, 0.232);
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| 122 |
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}.user-set td {color:rgb(255, 94, 0);text-align: left;
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| 123 |
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}.user-set td.value pre {color:rgb(255, 94, 0) !important;background-color: transparent !important;
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}.default td {color: black;text-align: left;
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| 125 |
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}.user-set td i,
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| 126 |
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.default td i {color: black;
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| 127 |
+
}.copy-paste-icon {background-image: url(data:image/svg+xml;base64,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);background-repeat: no-repeat;background-size: 14px 14px;background-position: 0;display: inline-block;width: 14px;height: 14px;cursor: pointer;
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}
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</style><body><div id="sk-container-id-21" class="sk-top-container" style="overflow: auto;"><div class="sk-text-repr-fallback"><pre>DecisionTreeClassifier(max_depth=6)</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-21" type="checkbox" checked><label for="sk-estimator-id-21" class="sk-toggleable__label fitted sk-toggleable__label-arrow"><div><div>DecisionTreeClassifier</div></div><div><a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.7/modules/generated/sklearn.tree.DecisionTreeClassifier.html">?<span>Documentation for DecisionTreeClassifier</span></a><span class="sk-estimator-doc-link fitted">i<span>Fitted</span></span></div></label><div class="sk-toggleable__content fitted" data-param-prefix=""><div class="estimator-table"><details><summary>Parameters</summary><table class="parameters-table"><tbody><tr class="default"><td><i class="copy-paste-icon"onclick="copyToClipboard('criterion',this.parentElement.nextElementSibling)"></i></td><td class="param">criterion </td><td class="value">'gini'</td></tr><tr class="default"><td><i class="copy-paste-icon"onclick="copyToClipboard('splitter',this.parentElement.nextElementSibling)"></i></td><td class="param">splitter </td><td class="value">'best'</td></tr><tr class="user-set"><td><i class="copy-paste-icon"onclick="copyToClipboard('max_depth',this.parentElement.nextElementSibling)"></i></td><td class="param">max_depth </td><td class="value">6</td></tr><tr class="default"><td><i class="copy-paste-icon"onclick="copyToClipboard('min_samples_split',this.parentElement.nextElementSibling)"></i></td><td class="param">min_samples_split </td><td class="value">2</td></tr><tr class="default"><td><i class="copy-paste-icon"onclick="copyToClipboard('min_samples_leaf',this.parentElement.nextElementSibling)"></i></td><td class="param">min_samples_leaf </td><td class="value">1</td></tr><tr class="default"><td><i class="copy-paste-icon"onclick="copyToClipboard('min_weight_fraction_leaf',this.parentElement.nextElementSibling)"></i></td><td class="param">min_weight_fraction_leaf </td><td class="value">0.0</td></tr><tr class="default"><td><i class="copy-paste-icon"onclick="copyToClipboard('max_features',this.parentElement.nextElementSibling)"></i></td><td class="param">max_features </td><td class="value">None</td></tr><tr class="default"><td><i class="copy-paste-icon"onclick="copyToClipboard('random_state',this.parentElement.nextElementSibling)"></i></td><td class="param">random_state </td><td class="value">None</td></tr><tr class="default"><td><i class="copy-paste-icon"onclick="copyToClipboard('max_leaf_nodes',this.parentElement.nextElementSibling)"></i></td><td class="param">max_leaf_nodes </td><td class="value">None</td></tr><tr class="default"><td><i class="copy-paste-icon"onclick="copyToClipboard('min_impurity_decrease',this.parentElement.nextElementSibling)"></i></td><td class="param">min_impurity_decrease </td><td class="value">0.0</td></tr><tr class="default"><td><i class="copy-paste-icon"onclick="copyToClipboard('class_weight',this.parentElement.nextElementSibling)"></i></td><td class="param">class_weight </td><td class="value">None</td></tr><tr class="default"><td><i class="copy-paste-icon"onclick="copyToClipboard('ccp_alpha',this.parentElement.nextElementSibling)"></i></td><td class="param">ccp_alpha </td><td class="value">0.0</td></tr><tr class="default"><td><i class="copy-paste-icon"onclick="copyToClipboard('monotonic_cst',this.parentElement.nextElementSibling)"></i></td><td class="param">monotonic_cst </td><td class="value">None</td></tr></tbody></table></details></div></div></div></div></div></div><script>function copyToClipboard(text, element) {// Get the parameter prefix from the closest toggleable contentconst toggleableContent = element.closest('.sk-toggleable__content');const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';const fullParamName = paramPrefix ? `${paramPrefix}${text}` : text;const originalStyle = element.style;const computedStyle = window.getComputedStyle(element);const originalWidth = computedStyle.width;const originalHTML = element.innerHTML.replace('Copied!', '');navigator.clipboard.writeText(fullParamName).then(() => {element.style.width = originalWidth;element.style.color = 'green';element.innerHTML = "Copied!";setTimeout(() => {element.innerHTML = originalHTML;element.style = originalStyle;}, 2000);}).catch(err => {console.error('Failed to copy:', err);element.style.color = 'red';element.innerHTML = "Failed!";setTimeout(() => {element.innerHTML = originalHTML;element.style = originalStyle;}, 2000);});return false;
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}document.querySelectorAll('.fa-regular.fa-copy').forEach(function(element) {const toggleableContent = element.closest('.sk-toggleable__content');const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';const paramName = element.parentElement.nextElementSibling.textContent.trim();const fullParamName = paramPrefix ? `${paramPrefix}${paramName}` : paramName;element.setAttribute('title', fullParamName);
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| 131 |
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});
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| 132 |
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</script></body>
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| 133 |
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| 134 |
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## Evaluation Results
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| 135 |
+
|
| 136 |
+
[More Information Needed]
|
| 137 |
+
|
| 138 |
+
# How to Get Started with the Model
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| 139 |
+
|
| 140 |
+
[More Information Needed]
|
| 141 |
+
|
| 142 |
+
# Model Card Authors
|
| 143 |
+
|
| 144 |
+
oforidavid
|
| 145 |
+
|
| 146 |
+
# Model Card Contact
|
| 147 |
+
|
| 148 |
+
You can contact the model card authors through following channels:
|
| 149 |
+
[More Information Needed]
|
| 150 |
+
|
| 151 |
+
# Citation
|
| 152 |
+
|
| 153 |
+
Below you can find information related to citation.
|
| 154 |
+
|
| 155 |
+
**BibTeX:**
|
| 156 |
+
```
|
| 157 |
+
[More Information Needed]
|
| 158 |
+
```
|
| 159 |
+
|
| 160 |
+
# Intended uses & limitations
|
| 161 |
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| 162 |
+
This model is made for educational purposes and is not ready to be used in production.
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config.json
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| 1 |
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{"sklearn": {"columns": ["x0", "x1", "char"], "environment": ["scikit-learn=1.0.2"], "example_input": {"Name": ["James", "John", "Robert"], "Gender": ["M", "F", "M"], "Count": [5304407, 5260831, 4970386], "Probability": [0.01451679, 0.01439753, 0.01360266]}, "model": {"file": "model.pkl"}, "task": "training-classification"}}
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model.pkl
ADDED
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@@ -0,0 +1,3 @@
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| 1 |
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version https://git-lfs.github.com/spec/v1
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| 2 |
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oid sha256:05ed50cb80c7c72426e6cea7a90672f04437f8b2ef1ca01353bd7d2304c172dc
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| 3 |
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size 19807
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namegender.csv
ADDED
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The diff for this file is too large to render.
See raw diff
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