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@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+.ipynb_checkpoints/plot-checkpoint.png filter=lfs diff=lfs merge=lfs -text
+plot.png filter=lfs diff=lfs merge=lfs -text

.ipynb_checkpoints/README-checkpoint.md

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+{
+ "cells": [],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

.ipynb_checkpoints/config-checkpoint.json

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+{
+    "sklearn": {
+        "columns": [
+            "Height",
+            "Age"
+        ],
+        "environment": [
+            "scikit-learn==1.3.0"
+        ],
+        "example_input": {
+            "Height": [
+                1.75,
+                1.65,
+                1.82
+            ],
+            "Age": [
+                22,
+                30,
+                45
+            ]
+        },
+        "model": {
+            "file": "regr.pkl"
+        }
+    },
+    "task": "tabular-regression",
+    "dataset": "ObesityDataSet_raw_and_data_sinthetic.csv",
+    "author": "Andres Henao"
+}

README.md

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "f12d78c8-bf84-4071-b14f-9f4a3f779c18",
+   "metadata": {},
+   "source": [
+    "---\n",
+    "license: mit\n",
+    "library_name: scikit-learn\n",
+    "tags:\n",
+    "  - regression\n",
+    "  - linear-regression\n",
+    "datasets:\n",
+    "  - ObesityDataSet_raw_and_data_sinhtetic.csv\n",
+    "model-index:\n",
+    "  - name: Obesity Weight Prediction Model\n",
+    "    results:\n",
+    "      - task:\n",
+    "          type: regression\n",
+    "          name: Weight prediction (kg)\n",
+    "        dataset:\n",
+    "          name: ObesityDataSet_raw_and_data_sinhtetic.csv\n",
+    "        metrics:\n",
+    "          - type: mean_squared_error\n",
+    "            value: 511.55\n",
+    "          - type: r2\n",
+    "            value: 0.2777\n",
+    "---\n",
+    "\n",
+    "# Obesity Weight Prediction Model — Linear Regression\n",
+    "\n",
+    "## Overview\n",
+    "This model predicts a person’s **weight (kg)** based on **height (m)** and **age (years)** using a Linear Regression model from scikit-learn.  \n",
+    "\n",
+    "---\n",
+    "\n",
+    "## Training\n",
+    "\n",
+    "| Detail | Value |\n",
+    "|--------|-------|\n",
+    "| Algorithm | `LinearRegression()` |\n",
+    "| Features | Height, Age |\n",
+    "| Target | Weight |\n",
+    "| Train/Test Split | 75% / 25% |\n",
+    "| Random State | 42 |\n",
+    "| Dataset | ObesityDataSet_raw_and_data_sinhtetic.csv |\n",
+    "\n",
+    "---\n",
+    "\n",
+    "## Performance\n",
+    "\n",
+    "| Metric | Score |\n",
+    "|--------|-------|\n",
+    "| MSE (Mean Squared Error) | **511.55** |\n",
+    "| R^2 Score | **0.2777** |\n",
+    "\n",
+    "These results indicate that height and age alone **do not fully explain** weight — important factors like diet, genetics, and exercise are missing.\n",
+    "\n",
+    "---\n",
+    "\n",
+    "## Visualization\n",
+    "\n",
+    "Below is a scatter plot showing predicted vs true weights:\n",
+    "\n",
+    "![True vs Predicted Weight](plot.png)\n",
+    "\n",
+    "The wide spread around the regression line shows prediction uncertainty for heavier individuals.\n",
+    "\n",
+    "---\n",
+    "\n",
+    "## Limitations\n",
+    "- Only two features used → reduced explanatory power  \n",
+    "- Synthetic dataset — not reflective of real population variation  \n",
+    "- Performance not suitable for real-world medical decisions  \n",
+    "\n",
+    "This model is intended for **educational use only**.\n",
+    "\n",
+    "---\n",
+    "## Strengths\n",
+    "- Easy to interpret\n",
+    "- Fast and simple\n",
+    "- Good educational model\n",
+    "\n",
+    "## Weaknesses\n",
+    "- Low accuracy\n",
+    "- Missing key health variables\n",
+    "- Not production-ready\n",
+    "\n",
+    "## Citation \n",
+    "- \"Estimation of Obesity Levels Based On Eating Habits and Physical Condition .\" UCI Machine Learning Repository, 2019, https://doi.org/10.24432/C5H31Z.\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "51036e3d-c32b-4102-b965-9759eb873131",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

config.json

@@ -0,0 +1,29 @@
+{
+    "sklearn": {
+        "columns": [
+            "Height",
+            "Age"
+        ],
+        "environment": [
+            "scikit-learn==1.3.0"
+        ],
+        "example_input": {
+            "Height": [
+                1.75,
+                1.65,
+                1.82
+            ],
+            "Age": [
+                22,
+                30,
+                45
+            ]
+        },
+        "model": {
+            "file": "regr.pkl"
+        }
+    },
+    "task": "tabular-regression",
+    "dataset": "ObesityDataSet_raw_and_data_sinthetic.csv",
+    "author": "Andres Henao"
+}

regr.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0e25851a2a4e0845328f879e1072fe6df079be8a286b13c4f8c36bc73c7cf515
+size 857