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  1. README.md +226 -0
  2. config.json +106 -0
  3. confusion_matrix.png +0 -0
  4. model.pkl +3 -0
README.md ADDED
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+ ---
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+ library_name: sklearn
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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.pkl
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+ widget:
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+ - structuredData:
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+ blue_aggressiveness_score:
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+ - 1.292
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+ - 1.0
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+ - 1.115
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+ blue_avg_durability:
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+ - 4.8
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+ - 5.2
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+ - 5.2
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+ blue_avg_offense:
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+ - 6.2
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+ - 5.2
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+ - 5.8
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+ blue_early_mid_ratio:
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+ - 1.0
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+ - 0.667
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+ - 1.5
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+ blue_mid_late_ratio:
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+ - 1.5
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+ - 1.5
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+ - 2.0
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+ control_effects_diff:
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+ - -22
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+ - 0
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+ - -2
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+ difficulty_diff:
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+ - 7
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+ - 0
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+ - 5
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+ durability_diff:
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+ - -8
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+ - -11
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+ - 3
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+ offense_diff:
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+ - 5
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+ - 6
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+ - 0
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+ power_spike_diff:
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+ - -1
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+ - -1
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+ - -3
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+ red_aggressiveness_score:
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+ - 0.812
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+ - 0.541
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+ - 1.261
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+ red_avg_durability:
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+ - 6.4
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+ - 7.4
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+ - 4.6
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+ red_avg_offense:
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+ - 5.2
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+ - 4.0
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+ - 5.8
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+ red_early_mid_ratio:
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+ - 1.0
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+ - 1.333
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+ - 0.5
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+ red_mid_late_ratio:
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+ - 4.0
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+ - 3.0
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+ - 1.333
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+ ---
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+
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+ # Model description
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+
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+ This is a RandomForestClassifier model trained on mpl_id_s14 dataset.
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+
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+ ## Intended uses & limitations
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+
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+ [More Information Needed]
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+
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+ ## Training Procedure
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+
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+ [More Information Needed]
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+
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+ ### Hyperparameters
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+
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+ <details>
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+ <summary> Click to expand </summary>
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+
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+ | Hyperparameter | Value |
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+ |--------------------------|---------|
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+ | bootstrap | True |
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+ | ccp_alpha | 0.0 |
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+ | class_weight | |
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+ | criterion | gini |
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+ | max_depth | 2 |
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+ | max_features | sqrt |
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+ | max_leaf_nodes | |
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+ | max_samples | |
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+ | min_impurity_decrease | 0.0 |
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+ | min_samples_leaf | 8 |
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+ | min_samples_split | 2 |
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+ | min_weight_fraction_leaf | 0.0 |
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+ | monotonic_cst | |
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+ | n_estimators | 50 |
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+ | n_jobs | |
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+ | oob_score | False |
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+ | random_state | 91 |
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+ | verbose | 0 |
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+ | warm_start | False |
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+
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+ </details>
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+
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+ ### Model Plot
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+
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+ <style>#sk-container-id-2 {/* 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;}
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+ }#sk-container-id-2 {color: var(--sklearn-color-text);
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+ }#sk-container-id-2 pre {padding: 0;
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+ }#sk-container-id-2 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-2 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-2 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-2 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-2 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-2 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-2 div.sk-parallel-item {display: flex;flex-direction: column;
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+ }#sk-container-id-2 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;
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+ }#sk-container-id-2 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;
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+ }#sk-container-id-2 div.sk-parallel-item:only-child::after {width: 0;
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+ }/* Serial-specific style estimator block */#sk-container-id-2 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-2 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-2 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.5em;box-sizing: border-box;text-align: center;
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+ }#sk-container-id-2 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-2 label.sk-toggleable__label-arrow:hover:before {color: var(--sklearn-color-text);
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+ }/* Toggleable content - dropdown */#sk-container-id-2 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;/* unfitted */background-color: var(--sklearn-color-unfitted-level-0);
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+ }#sk-container-id-2 div.sk-toggleable__content.fitted {/* fitted */background-color: var(--sklearn-color-fitted-level-0);
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+ }#sk-container-id-2 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-2 div.sk-toggleable__content.fitted pre {/* unfitted */background-color: var(--sklearn-color-fitted-level-0);
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+ }#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {/* Expand drop-down */max-height: 200px;max-width: 100%;overflow: auto;
147
+ }#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: "▾";
148
+ }/* Pipeline/ColumnTransformer-specific style */#sk-container-id-2 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);
149
+ }#sk-container-id-2 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: var(--sklearn-color-fitted-level-2);
150
+ }/* Estimator-specific style *//* Colorize estimator box */
151
+ #sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {/* unfitted */background-color: var(--sklearn-color-unfitted-level-2);
152
+ }#sk-container-id-2 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {/* fitted */background-color: var(--sklearn-color-fitted-level-2);
153
+ }#sk-container-id-2 div.sk-label label.sk-toggleable__label,
154
+ #sk-container-id-2 div.sk-label label {/* The background is the default theme color */color: var(--sklearn-color-text-on-default-background);
155
+ }/* On hover, darken the color of the background */
156
+ #sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {color: var(--sklearn-color-text);background-color: var(--sklearn-color-unfitted-level-2);
157
+ }/* Label box, darken color on hover, fitted */
158
+ #sk-container-id-2 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {color: var(--sklearn-color-text);background-color: var(--sklearn-color-fitted-level-2);
159
+ }/* Estimator label */#sk-container-id-2 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;
160
+ }#sk-container-id-2 div.sk-label-container {text-align: center;
161
+ }/* Estimator-specific */
162
+ #sk-container-id-2 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);
163
+ }#sk-container-id-2 div.sk-estimator.fitted {/* fitted */background-color: var(--sklearn-color-fitted-level-0);
164
+ }/* on hover */
165
+ #sk-container-id-2 div.sk-estimator:hover {/* unfitted */background-color: var(--sklearn-color-unfitted-level-2);
166
+ }#sk-container-id-2 div.sk-estimator.fitted:hover {/* fitted */background-color: var(--sklearn-color-fitted-level-2);
167
+ }/* Specification for estimator info (e.g. "i" and "?") *//* Common style for "i" and "?" */.sk-estimator-doc-link,
168
+ a:link.sk-estimator-doc-link,
169
+ 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);
170
+ }.sk-estimator-doc-link.fitted,
171
+ a:link.sk-estimator-doc-link.fitted,
172
+ a:visited.sk-estimator-doc-link.fitted {/* fitted */border: var(--sklearn-color-fitted-level-1) 1pt solid;color: var(--sklearn-color-fitted-level-1);
173
+ }/* On hover */
174
+ div.sk-estimator:hover .sk-estimator-doc-link:hover,
175
+ .sk-estimator-doc-link:hover,
176
+ div.sk-label-container:hover .sk-estimator-doc-link:hover,
177
+ .sk-estimator-doc-link:hover {/* unfitted */background-color: var(--sklearn-color-unfitted-level-3);color: var(--sklearn-color-background);text-decoration: none;
178
+ }div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,
179
+ .sk-estimator-doc-link.fitted:hover,
180
+ div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,
181
+ .sk-estimator-doc-link.fitted:hover {/* fitted */background-color: var(--sklearn-color-fitted-level-3);color: var(--sklearn-color-background);text-decoration: none;
182
+ }/* 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);
184
+ }.sk-estimator-doc-link.fitted span {/* fitted */background: var(--sklearn-color-fitted-level-0);border: var(--sklearn-color-fitted-level-3);
185
+ }.sk-estimator-doc-link:hover span {display: block;
186
+ }/* "?"-specific style due to the `<a>` HTML tag */#sk-container-id-2 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;
187
+ }#sk-container-id-2 a.estimator_doc_link.fitted {/* fitted */border: var(--sklearn-color-fitted-level-1) 1pt solid;color: var(--sklearn-color-fitted-level-1);
188
+ }/* On hover */
189
+ #sk-container-id-2 a.estimator_doc_link:hover {/* unfitted */background-color: var(--sklearn-color-unfitted-level-3);color: var(--sklearn-color-background);text-decoration: none;
190
+ }#sk-container-id-2 a.estimator_doc_link.fitted:hover {/* fitted */background-color: var(--sklearn-color-fitted-level-3);
191
+ }
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+ </style><div id="sk-container-id-2" class="sk-top-container" style="overflow: auto;"><div class="sk-text-repr-fallback"><pre>RandomForestClassifier(max_depth=2, min_samples_leaf=8, n_estimators=50,random_state=91)</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-2" type="checkbox" checked><label for="sk-estimator-id-2" 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/1.5/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(max_depth=2, min_samples_leaf=8, n_estimators=50,random_state=91)</pre></div> </div></div></div></div>
193
+
194
+ ## Evaluation Results
195
+
196
+ [More Information Needed]
197
+
198
+ # How to Get Started with the Model
199
+
200
+ [More Information Needed]
201
+
202
+ # Model Card Authors
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+
204
+ z4fL
205
+
206
+ # Model Card Contact
207
+
208
+ You can contact the model card authors through following channels:
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+ [More Information Needed]
210
+
211
+ # Citation
212
+
213
+ Below you can find information related to citation.
214
+
215
+ **BibTeX:**
216
+ ```
217
+ [More Information Needed]
218
+ ```
219
+
220
+ # Limitations
221
+
222
+ This model is only trained with MPL ID Season 14 data
223
+
224
+ # confusion_matrix
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+
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+ ![confusion_matrix](confusion_matrix.png)
config.json ADDED
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+ {
2
+ "sklearn": {
3
+ "columns": [
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+ "durability_diff",
5
+ "offense_diff",
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+ "control_effects_diff",
7
+ "difficulty_diff",
8
+ "power_spike_diff",
9
+ "blue_avg_durability",
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+ "red_avg_durability",
11
+ "blue_avg_offense",
12
+ "red_avg_offense",
13
+ "blue_aggressiveness_score",
14
+ "red_aggressiveness_score",
15
+ "blue_early_mid_ratio",
16
+ "blue_mid_late_ratio",
17
+ "red_early_mid_ratio",
18
+ "red_mid_late_ratio"
19
+ ],
20
+ "environment": [
21
+ "scikit-learn=1.5.2"
22
+ ],
23
+ "example_input": {
24
+ "blue_aggressiveness_score": [
25
+ 1.292,
26
+ 1.0,
27
+ 1.115
28
+ ],
29
+ "blue_avg_durability": [
30
+ 4.8,
31
+ 5.2,
32
+ 5.2
33
+ ],
34
+ "blue_avg_offense": [
35
+ 6.2,
36
+ 5.2,
37
+ 5.8
38
+ ],
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+ "blue_early_mid_ratio": [
40
+ 1.0,
41
+ 0.667,
42
+ 1.5
43
+ ],
44
+ "blue_mid_late_ratio": [
45
+ 1.5,
46
+ 1.5,
47
+ 2.0
48
+ ],
49
+ "control_effects_diff": [
50
+ -22,
51
+ 0,
52
+ -2
53
+ ],
54
+ "difficulty_diff": [
55
+ 7,
56
+ 0,
57
+ 5
58
+ ],
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+ "durability_diff": [
60
+ -8,
61
+ -11,
62
+ 3
63
+ ],
64
+ "offense_diff": [
65
+ 5,
66
+ 6,
67
+ 0
68
+ ],
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+ "power_spike_diff": [
70
+ -1,
71
+ -1,
72
+ -3
73
+ ],
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+ "red_aggressiveness_score": [
75
+ 0.812,
76
+ 0.541,
77
+ 1.261
78
+ ],
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+ "red_avg_durability": [
80
+ 6.4,
81
+ 7.4,
82
+ 4.6
83
+ ],
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+ "red_avg_offense": [
85
+ 5.2,
86
+ 4.0,
87
+ 5.8
88
+ ],
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+ "red_early_mid_ratio": [
90
+ 1.0,
91
+ 1.333,
92
+ 0.5
93
+ ],
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+ "red_mid_late_ratio": [
95
+ 4.0,
96
+ 3.0,
97
+ 1.333
98
+ ]
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+ },
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+ "model": {
101
+ "file": "model.pkl"
102
+ },
103
+ "model_format": "pickle",
104
+ "task": "tabular-classification"
105
+ }
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+ }
confusion_matrix.png ADDED
model.pkl ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:b4d33b6f76d945bee2faa4d6e6f76eea3509a2e843aada7c4fc49feb7702a742
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+ size 895843