Update README.md

README.md

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-# Dataset Card for Dataset Name
+# 
+---
+# For reference on dataset card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/datasetcard.md?plain=1
+# Doc / guide: https://huggingface.co/docs/hub/datasets-cards
+{{ card_data }}
+---
+
+# Dataset Card for Estimation of Obesity Levels Based on Eating Habits and Physical Condition
 
 <!-- Provide a quick summary of the dataset. -->
 
-This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
+This dataset contains survey data collected from individuals in Mexico, Peru, and Colombia to estimate obesity levels based on eating habits and physical condition. It includes 2,111 rows and 17 columns with demographic, dietary, and lifestyle features, along with a categorical target variable for obesity levels.
 
 ## Dataset Details
 
 ### Dataset Description
 
-<!-- Provide a longer summary of what this dataset is. -->
-
+The dataset is designed to classify individuals into one of seven obesity-related categories based on their eating habits, physical activity, and demographics. It can be used for health informatics, predictive modeling, and educational purposes.
 
-
-- **Curated by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
+- **Curated by:** Angel Palacios, Edgar Moreira, and Rafael Barea  
+- **Funded by [optional]:** [More Information Needed]  
+- **Shared by [optional]:** UCI Machine Learning Repository  
+- **Language(s) (NLP):** Spanish (original survey), English (dataset)  
+- **License:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)  
 
 ### Dataset Sources [optional]
 
-<!-- Provide the basic links for the dataset. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+- **Repository:** [UCI Machine Learning Repository](https://archive.ics.uci.edu/dataset/544/estimation+of+obesity+levels+based+on+eating+habits+and+physical+condition)  
+- **Paper [optional]:** Palacios, A., Moreira, E., & Barea, R. (2019). "Estimation of Obesity Levels based on Eating Habits and Physical Condition."  
+- **Demo [optional]:** [More Information Needed]  
 
 ## Uses
 
-<!-- Address questions around how the dataset is intended to be used. -->
-
 ### Direct Use
 
-<!-- This section describes suitable use cases for the dataset. -->
-
-[More Information Needed]
+- Classification of obesity levels.  
+- Educational projects on data preprocessing and supervised learning.  
+- Research into the correlation between habits and obesity.  
 
 ### Out-of-Scope Use
 
-<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
-
-[More Information Needed]
+- Using the dataset to make clinical or diagnostic decisions.  
+- Using the dataset to stigmatize or discriminate individuals.  
 
 ## Dataset Structure
 
-<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
-
-[More Information Needed]
+- **Rows:** 2,111  
+- **Columns:** 17  
+- **Target Variable:** `NObeyesdad` (7 obesity categories)  
+
+**Class Distribution:**  
+- Obesity_Type_I: 351  
+- Obesity_Type_II: 297  
+- Obesity_Type_III: 324  
+- Overweight_Level_I: 290  
+- Overweight_Level_II: 290  
+- Normal_Weight: 287  
+- Insufficient_Weight: 272  
+
+**Key Fields:**  
+- Gender, Age, Height, Weight  
+- family_history_with_overweight  
+- FAVC (Frequent high-calorie food consumption)  
+- FCVC (Vegetable consumption frequency)  
+- NCP (Number of main meals)  
+- CAEC (Consumption of food between meals)  
+- SMOKE, CH2O (water intake), SCC (calories monitoring)  
+- FAF (Physical activity frequency), TUE (Time on devices)  
+- CALC (Alcohol consumption), MTRANS (Transportation)  
+- NObeyesdad (Obesity classification)  
 
 ## Dataset Creation
 
 ### Curation Rationale
 
-<!-- Motivation for the creation of this dataset. -->
-
-[More Information Needed]
+The dataset was created to explore the relationship between lifestyle, eating habits, and obesity levels in Latin America.
 
 ### Source Data
 
-<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
-
 #### Data Collection and Processing
 
-<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
-
-[More Information Needed]
+Data was collected through surveys administered in Mexico, Peru, and Colombia. BMI and other lifestyle metrics were used to derive obesity levels.
 
 #### Who are the source data producers?
 
-<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
-
-[More Information Needed]
+Adults from the surveyed countries who self-reported their eating and lifestyle habits.
 
 ### Annotations [optional]
 
-<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
-
 #### Annotation process
 
-<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
-
-[More Information Needed]
+Obesity levels were derived from BMI categories and participant data.
 
 #### Who are the annotators?
 
-<!-- This section describes the people or systems who created the annotations. -->
-
-[More Information Needed]
+Researchers from UCI and collaborators.
 
 #### Personal and Sensitive Information
 
-<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
-
-[More Information Needed]
+Contains sensitive health-related information (weight, eating habits, lifestyle). Does not contain personally identifiable information.
 
 ## Bias, Risks, and Limitations
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
+- Data is self-reported (possible inaccuracies).  
+- Population limited to three Latin American countries.  
+- Not representative of global populations.  
 
 ### Recommendations
 
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
+Users should be made aware of the risks, biases, and limitations of the dataset. The dataset is intended for educational and research purposes, not medical diagnosis.
 
 ## Citation [optional]
 
-<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
-
 **BibTeX:**
 
-[More Information Needed]
-
-**APA:**
-
-[More Information Needed]
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
-
-[More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
-
-## Dataset Card Authors [optional]
-
-[More Information Needed]
-
-## Dataset Card Contact
-
-[More Information Needed]
+```bibtex
+@misc{palacios2019obesity,
+  title={Estimation of Obesity Levels Based on Eating Habits and Physical Condition},
+  author={Palacios, Angel and Moreira, Edgar and Barea, Rafael},
+  year={2019},
+  publisher={UCI Machine Learning Repository},
+  howpublished={\url{https://archive.ics.uci.edu/ml/datasets/Estimation+of+obesity+levels+based+on+eating+habits+and+physical+condition}}
+}