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README.md

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-    "---\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"
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+---
+license: mit
+library_name: scikit-learn
+tags:
+- regression
+- linear-regression
+- obesity
+datasets:
+- ObesityDataSet_raw_and_data_sinthetic.csv
+model-index:
+- name: Obesity Weight Prediction Model
+  results:
+  - task:
+      type: regression
+      name: Weight prediction (kg)
+    dataset:
+      name: ObesityDataSet_raw_and_data_sinthetic.csv
+      type: tabular
+    metrics:
+    - type: mean_squared_error
+      value: 511.55
+    - type: r2
+      value: 0.2777
+---
+
+# Obesity Weight Prediction Model — Linear Regression
+
+## Overview
+This model predicts a person’s **weight (kg)** based on **height (m)** and **age (years)** using a Linear Regression model from scikit-learn.  
+
+---
+
+## Training
+
+| Detail | Value |
+|--------|-------|
+| Algorithm | `LinearRegression()` |
+| Features | Height, Age |
+| Target | Weight |
+| Train/Test Split | 75% / 25% |
+| Random State | 42 |
+| Dataset | ObesityDataSet_raw_and_data_sinhtetic.csv |
+
+---
+
+## Performance
+
+| Metric | Score |
+|--------|-------|
+| MSE (Mean Squared Error) | **511.55** |
+| R^2 Score | **0.2777** |
+
+These results indicate that height and age alone **do not fully explain** weight — important factors like diet, genetics, and exercise are missing.
+
+---
+
+## Visualization
+
+Below is a scatter plot showing predicted vs true weights:
+
+![True vs Predicted Weight](plot.png)
+
+The wide spread around the regression line shows prediction uncertainty for heavier individuals.
+
+---
+
+## Limitations
+- Only two features used → reduced explanatory power  
+- Synthetic dataset — not reflective of real population variation  
+- Performance not suitable for real-world medical decisions  
+
+This model is intended for **educational use only**.
+
+---
+## Strengths
+- Easy to interpret
+- Fast and simple
+- Good educational model
+
+## Weaknesses
+- Low accuracy
+- Missing key health variables
+- Not production-ready
+
+## Citation 
+- "Estimation of Obesity Levels Based On Eating Habits and Physical Condition ." UCI Machine Learning Repository, 2019, https://doi.org/10.24432/C5H31Z.
+