Update README.md

README.md

@@ -21,13 +21,13 @@ configs:
     path: "labeled_splits/test.csv"
     description: "A stratified splitting of the labeled data."
 ---
-# 🌱 GreenHySpectra: A multi-source hyperspectral dataset for global vegetation trait prediction 🌱
+# 🌱 GreenHyperSpectra: A multi-source hyperspectral dataset for global vegetation trait prediction 🌱
 
 GreenHySpectra is a collection of hyperspectral reflectance data of vegetation from different sources. It is intended for Regression machine learning task for plant trait prediction with self and semi-supervised learning.
 
 ## 📁 Configurations
-### 1. `GreenHySpectra: Unlabeled Set`
-- Files: all CSVs under `unlb/`
+### 1. `GreenHyperSpectra: Unlabeled set`
+- Files: all CSVs under `unlabeled/`
 - Contains:
   - Sample ID
   - Spectral bands (400-2450 nm) >> 1721 bands
@@ -39,7 +39,7 @@ GreenHySpectra is a collection of hyperspectral reflectance data of vegetation f
 | 2450           | Reflectance at 2450nm                   |
 ---
 ### 2. `Labeled set`
-- File: `50_all_traits.csv`
+- File: `labeled/all.csv`
 - Contains:
   - Sample ID
   - Dataset ID
@@ -60,5 +60,14 @@ GreenHySpectra is a collection of hyperspectral reflectance data of vegetation f
 | Car            | Leaf carotenoids content (µg/m²)        |
 | Anth           | Leaf anthocynins content (µg/m²)        |
 ---
+### 3. `Split labeled set`
+- Files: all CSVs under `labeled_splits/`
+These files follow the same format as the previous set but are pre-split for machine learning purposes. The split is stratified based on the dataset ID, with 20% of the data reserved for testing.
+
+
+> ⚠️ **Note:** Due to the high dimensionality of spectral datasets—often containing hundreds or thousands of columns—**Hugging Face Data Studio may not render these files properly**. This is a known limitation, as the Studio interface is not optimized for wide tabular data.  
+>
+> To work effectively with this dataset, we recommend using the **Hugging Face `datasets` library** or the **MLCroissant Python library** for programmatic access and exploration.
+
 license: cc-by-nc-4.0
 ---