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README.md

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+---
+library_name: sklearn
+tags:
+- sklearn
+- skops
+- tabular-classification
+model_format: pickle
+model_file: model.pkl
+widget:
+  structuredData:
+    Month:
+    - 5.0
+    - 4.0
+    - 10.0
+    Quantity:
+    - 4.0
+    - 2.0
+    - 2.0
+    Seller:
+    - 8.0
+    - 8.0
+    - 3.0
+    Total Cost:
+    - 2146.0
+    - 4216.2
+    - 9480.0
+    Week:
+    - 17.0
+    - 13.0
+    - 40.0
+    Year:
+    - 2022.0
+    - 2022.0
+    - 2022.0
+---
+
+# 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     |
+|------------------|-----------|
+| algorithm        | auto      |
+| leaf_size        | 30        |
+| metric           | manhattan |
+| metric_params    |           |
+| n_jobs           |           |
+| n_neighbors      | 10        |
+| p                | 2         |
+| weights          | distance  |
+
+</details>
+
+### Model Plot
+
+<style>#sk-container-id-13 {color: black;}#sk-container-id-13 pre{padding: 0;}#sk-container-id-13 div.sk-toggleable {background-color: white;}#sk-container-id-13 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-13 label.sk-toggleable__label-arrow:before {content: "▸";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-13 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-13 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-13 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-13 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-13 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-13 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: "▾";}#sk-container-id-13 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-13 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-13 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-13 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-13 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-13 div.sk-parallel-item::after {content: "";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-13 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-13 div.sk-serial::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-13 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-13 div.sk-item {position: relative;z-index: 1;}#sk-container-id-13 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-13 div.sk-item::before, #sk-container-id-13 div.sk-parallel-item::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-13 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-13 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-13 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-13 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-13 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-13 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-13 div.sk-label-container {text-align: center;}#sk-container-id-13 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 the default 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-13 div.sk-text-repr-fallback {display: none;}</style><div id="sk-container-id-13" class="sk-top-container" style="overflow: auto;"><div class="sk-text-repr-fallback"><pre>KNeighborsRegressor(metric=&#x27;manhattan&#x27;, n_neighbors=10, weights=&#x27;distance&#x27;)</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 sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-13" type="checkbox" checked><label for="sk-estimator-id-13" class="sk-toggleable__label sk-toggleable__label-arrow">KNeighborsRegressor</label><div class="sk-toggleable__content"><pre>KNeighborsRegressor(metric=&#x27;manhattan&#x27;, n_neighbors=10, weights=&#x27;distance&#x27;)</pre></div></div></div></div></div>
+
+## Evaluation Results
+
+| Metric    |   Value |
+|-----------|---------|
+| accuracy  |   0.717 |
+| r squared |   0.717 |
+
+# 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]
+```
+
+# model_description
+
+This is a K-Nearest Neighbour Regressor trained to identify inventory-delay time.
+
+# limitations
+
+This model is trained for educational purposes.

config.json

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+{
+    "sklearn": {
+        "columns": [
+            "Seller",
+            "Total Cost",
+            "Quantity",
+            "Month",
+            "Week",
+            "Year"
+        ],
+        "environment": [
+            "scikit-learn"
+        ],
+        "example_input": {
+            "Month": [
+                5.0,
+                4.0,
+                10.0
+            ],
+            "Quantity": [
+                4.0,
+                2.0,
+                2.0
+            ],
+            "Seller": [
+                8.0,
+                8.0,
+                3.0
+            ],
+            "Total Cost": [
+                2146.0,
+                4216.2,
+                9480.0
+            ],
+            "Week": [
+                17.0,
+                13.0,
+                40.0
+            ],
+            "Year": [
+                2022.0,
+                2022.0,
+                2022.0
+            ]
+        },
+        "model": {
+            "file": "model.pkl"
+        },
+        "model_format": "pickle",
+        "task": "tabular-classification",
+        "use_intelex": false
+    }
+}

model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:575c393309248f5dc98609aba3b899f3e69ab12b8992b3a7a19483f704deed4c
+size 13510