update model

README.md

@@ -0,0 +1,226 @@
+---
+library_name: sklearn
+tags:
+- sklearn
+- skops
+- tabular-classification
+model_format: pickle
+model_file: hw4_baseline_regressor.pkl
+widget:
+- structuredData:
+    households:
+    - 254.0
+    - 957.0
+    - 801.0
+    housing_median_age:
+    - 20.0
+    - 2.0
+    - 31.0
+    latitude:
+    - 32.79
+    - 38.01
+    - 33.92
+    longitude:
+    - -117.24
+    - -121.29
+    - -118.14
+    median_income:
+    - 3.1838
+    - 4.4871
+    - 3.2237
+    ocean_proximity_<1H OCEAN:
+    - false
+    - false
+    - true
+    ocean_proximity_INLAND:
+    - false
+    - true
+    - false
+    ocean_proximity_ISLAND:
+    - false
+    - false
+    - false
+    ocean_proximity_NEAR BAY:
+    - false
+    - false
+    - false
+    ocean_proximity_NEAR OCEAN:
+    - true
+    - false
+    - false
+    population:
+    - 525.0
+    - 3327.0
+    - 2313.0
+    total_bedrooms:
+    - 278.0
+    - 1116.0
+    - 853.0
+    total_rooms:
+    - 961.0
+    - 6403.0
+    - 3731.0
+---
+
+# Model description
+
+[More Information Needed]
+
+## Intended uses & limitations
+
+[More Information Needed]
+
+## Training Procedure
+
+[More Information Needed]
+
+### Hyperparameters
+
+<details>
+<summary> Click to expand </summary>
+
+| Hyperparameter               | Value                                                           |
+|------------------------------|-----------------------------------------------------------------|
+| memory                       |                                                                 |
+| steps                        | [('scaler', StandardScaler()), ('rf', RandomForestRegressor())] |
+| verbose                      | False                                                           |
+| scaler                       | StandardScaler()                                                |
+| rf                           | RandomForestRegressor()                                         |
+| scaler__copy                 | True                                                            |
+| scaler__with_mean            | True                                                            |
+| scaler__with_std             | True                                                            |
+| rf__bootstrap                | True                                                            |
+| rf__ccp_alpha                | 0.0                                                             |
+| rf__criterion                | squared_error                                                   |
+| rf__max_depth                |                                                                 |
+| rf__max_features             | 1.0                                                             |
+| rf__max_leaf_nodes           |                                                                 |
+| rf__max_samples              |                                                                 |
+| rf__min_impurity_decrease    | 0.0                                                             |
+| rf__min_samples_leaf         | 1                                                               |
+| rf__min_samples_split        | 2                                                               |
+| rf__min_weight_fraction_leaf | 0.0                                                             |
+| rf__monotonic_cst            |                                                                 |
+| rf__n_estimators             | 100                                                             |
+| rf__n_jobs                   |                                                                 |
+| rf__oob_score                | False                                                           |
+| rf__random_state             |                                                                 |
+| rf__verbose                  | 0                                                               |
+| rf__warm_start               | False                                                           |
+
+</details>
+
+### Model Plot
+
+<style>#sk-container-id-3 {/* 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-3 {color: var(--sklearn-color-text);
+}#sk-container-id-3 pre {padding: 0;
+}#sk-container-id-3 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-3 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-3 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-3 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-3 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-3 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: var(--sklearn-color-background);position: relative;
+}#sk-container-id-3 div.sk-parallel-item {display: flex;flex-direction: column;
+}#sk-container-id-3 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;
+}#sk-container-id-3 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;
+}#sk-container-id-3 div.sk-parallel-item:only-child::after {width: 0;
+}/* Serial-specific style estimator block */#sk-container-id-3 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-3 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-3 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-3 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-3 label.sk-toggleable__label-arrow:hover:before {color: var(--sklearn-color-text);
+}/* Toggleable content - dropdown */#sk-container-id-3 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-3 div.sk-toggleable__content.fitted {/* fitted */background-color: var(--sklearn-color-fitted-level-0);
+}#sk-container-id-3 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-3 div.sk-toggleable__content.fitted pre {/* unfitted */background-color: var(--sklearn-color-fitted-level-0);
+}#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {/* Expand drop-down */max-height: 200px;max-width: 100%;overflow: auto;
+}#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: "▾";
+}/* Pipeline/ColumnTransformer-specific style */#sk-container-id-3 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-3 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-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {/* unfitted */background-color: var(--sklearn-color-unfitted-level-2);
+}#sk-container-id-3 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-3 div.sk-label label.sk-toggleable__label,
+#sk-container-id-3 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-3 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-3 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-3 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;
+}#sk-container-id-3 div.sk-label-container {text-align: center;
+}/* Estimator-specific */
+#sk-container-id-3 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-3 div.sk-estimator.fitted {/* fitted */background-color: var(--sklearn-color-fitted-level-0);
+}/* on hover */
+#sk-container-id-3 div.sk-estimator:hover {/* unfitted */background-color: var(--sklearn-color-unfitted-level-2);
+}#sk-container-id-3 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-3 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-3 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-3 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-3 a.estimator_doc_link.fitted:hover {/* fitted */background-color: var(--sklearn-color-fitted-level-3);
+}
+</style><div id="sk-container-id-3" class="sk-top-container" style="overflow: auto;"><div class="sk-text-repr-fallback"><pre>Pipeline(steps=[(&#x27;scaler&#x27;, StandardScaler()), (&#x27;rf&#x27;, RandomForestRegressor())])</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 sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-3" type="checkbox" ><label for="sk-estimator-id-3" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;&nbsp;Pipeline<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html">?<span>Documentation for Pipeline</span></a><span class="sk-estimator-doc-link fitted">i<span>Fitted</span></span></label><div class="sk-toggleable__content fitted"><pre>Pipeline(steps=[(&#x27;scaler&#x27;, StandardScaler()), (&#x27;rf&#x27;, RandomForestRegressor())])</pre></div> </div></div><div class="sk-serial"><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-4" type="checkbox" ><label for="sk-estimator-id-4" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;StandardScaler<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.StandardScaler.html">?<span>Documentation for StandardScaler</span></a></label><div class="sk-toggleable__content fitted"><pre>StandardScaler()</pre></div> </div></div><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-5" type="checkbox" ><label for="sk-estimator-id-5" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;RandomForestRegressor<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.5/modules/generated/sklearn.ensemble.RandomForestRegressor.html">?<span>Documentation for RandomForestRegressor</span></a></label><div class="sk-toggleable__content fitted"><pre>RandomForestRegressor()</pre></div> </div></div></div></div></div></div>
+
+## Evaluation Results
+
+| Metric   | Value   |
+|----------|---------|
+| f1 score |         |
+| accuracy |         |
+
+# How to Get Started with the Model
+
+[More Information Needed]
+
+# Model Card Authors
+
+This model card is written by following authors:
+
+[More Information Needed]
+
+# Model Card Contact
+
+You can contact the model card authors through following channels:
+[More Information Needed]
+
+# Citation
+
+Below you can find information related to citation.
+
+**BibTeX:**
+```
+[More Information Needed]
+```
+
+# eval_method
+
+The model is evaluated using test split, on accuracy and f1.

config.json

@@ -0,0 +1,94 @@
+{
+    "sklearn": {
+        "columns": [
+            "longitude",
+            "latitude",
+            "housing_median_age",
+            "total_rooms",
+            "total_bedrooms",
+            "population",
+            "households",
+            "median_income",
+            "ocean_proximity_<1H OCEAN",
+            "ocean_proximity_INLAND",
+            "ocean_proximity_ISLAND",
+            "ocean_proximity_NEAR BAY",
+            "ocean_proximity_NEAR OCEAN"
+        ],
+        "environment": [
+            "scikit-learn=1.5.2"
+        ],
+        "example_input": {
+            "households": [
+                254.0,
+                957.0,
+                801.0
+            ],
+            "housing_median_age": [
+                20.0,
+                2.0,
+                31.0
+            ],
+            "latitude": [
+                32.79,
+                38.01,
+                33.92
+            ],
+            "longitude": [
+                -117.24,
+                -121.29,
+                -118.14
+            ],
+            "median_income": [
+                3.1838,
+                4.4871,
+                3.2237
+            ],
+            "ocean_proximity_<1H OCEAN": [
+                false,
+                false,
+                true
+            ],
+            "ocean_proximity_INLAND": [
+                false,
+                true,
+                false
+            ],
+            "ocean_proximity_ISLAND": [
+                false,
+                false,
+                false
+            ],
+            "ocean_proximity_NEAR BAY": [
+                false,
+                false,
+                false
+            ],
+            "ocean_proximity_NEAR OCEAN": [
+                true,
+                false,
+                false
+            ],
+            "population": [
+                525.0,
+                3327.0,
+                2313.0
+            ],
+            "total_bedrooms": [
+                278.0,
+                1116.0,
+                853.0
+            ],
+            "total_rooms": [
+                961.0,
+                6403.0,
+                3731.0
+            ]
+        },
+        "model": {
+            "file": "hw4_baseline_regressor.pkl"
+        },
+        "model_format": "pickle",
+        "task": "tabular-classification"
+    }
+}

hw4_baseline_regressor.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:30e177da608ec1657c5ed726782e7df0f19f665ccb02792e1fd9f8c4927872b1
+size 125779013