update dataset card with metadata

README.md

@@ -1,30 +1,47 @@
+---
+language:
+- en
+license: apache-2.0
+task_categories:
+- tabular-classification
+tags:
+- healthcare
+- medical
+- thyroid
+- classification
+- tabular
+pretty_name: Thyroid Diff Clean Dataset
+size_categories:
+- 1K<n<10K
+---
+
 # Thyroid Diff Clean Dataset
 
 ## Description
-This dataset contains cleaned and preprocessed thyroid disease data.
-Categorical features have been encoded and missing values removed.
-The dataset is split into train and test sets for machine learning tasks.
+This dataset contains cleaned and preprocessed thyroid disease data prepared for machine learning tasks.  
+Categorical features are encoded and missing values have been handled.  
+The dataset includes a structured train–test split.
 
 ## Dataset Structure
-- train.csv
-- test.csv
+- train.csv — training split (80%)
+- test.csv — testing split (20%)
 
 ## Features
-The dataset includes clinical and diagnostic features related to thyroid condition prediction.
+The dataset includes clinical and diagnostic features related to thyroid condition prediction.  
 The target variable represents recurrence status.
 
 ## Preprocessing Steps
-- Removed duplicates
-- Dropped missing values
-- Encoded categorical variables
-- Stratified train-test split (80-20)
+- Removed duplicate records  
+- Handled missing values  
+- Encoded categorical variables  
+- Stratified train–test split (80–20)
 
 ## Intended Use
 This dataset is suitable for:
-- Classification tasks
-- Medical ML experiments
-- Educational purposes
-- Model benchmarking
+- Classification tasks  
+- Medical machine learning experiments  
+- Educational projects  
+- Benchmarking tabular ML models  
 
 ## License
 Apache-2.0