Add YAML metadata to fix dataset card warnings

README.md

@@ -1,3 +1,23 @@
+---
+license: mit
+task_categories:
+- time-series-forecasting
+- audio-classification
+language:
+- en
+tags:
+- rf-signals
+- radio
+- rtl-sdr
+- signal-processing
+- machine-learning
+- telecommunications
+- software-defined-radio
+pretty_name: RTL-ML RF Signal Classification Dataset
+size_categories:
+- 100K<n<1M
+---
+
 # RTL-ML Dataset
 
 ## Dataset Summary
@@ -47,12 +67,39 @@ sample = np.load(f"{dataset_path}/datasets_validated/ADS_B_0.npy")
 print(f"Signal shape: {sample.shape}")  # (1048576,) complex64
 ```
 
+## Dataset Structure
+
+```
+rtl-ml-dataset/
+└── datasets_validated/
+    ├── ADS_B_0.npy ... ADS_B_29.npy       (30 files)
+    ├── APRS_0.npy ... APRS_29.npy         (30 files)
+    ├── FM_broadcast_0.npy ... _29.npy     (30 files)
+    ├── ISM_sensors_0.npy ... _29.npy      (30 files)
+    ├── NOAA_APT_0.npy ... NOAA_APT_29.npy (30 files)
+    ├── NOAA_weather_0.npy ... _29.npy     (30 files)
+    ├── noise_0.npy ... noise_29.npy       (30 files)
+    └── pager_0.npy ... pager_29.npy       (30 files)
+```
+
+Each `.npy` file contains:
+- **Shape:** (1048576,) - 1 second @ 1.024 MSPS
+- **Dtype:** `complex64` (I/Q samples)
+- **Size:** ~8.4 MB per file
+
 ## Hardware
 
 - **SDR:** RTL-SDR Blog V4 ($39.95)
 - **Computer:** Indiedroid Nova 16GB ($179.95)
 - **Antenna:** Telescopic dipole (included)
 
+## Model Performance
+
+When trained with Random Forest (100 trees):
+- **Overall Accuracy:** 87.5%
+- **Perfect Classes:** ADS-B, FM, ISM, NOAA APT, Weather, Pager (100%)
+- **Challenging:** APRS ↔ Noise confusion (sparse packets)
+
 ## Citation
 
 ```bibtex
@@ -73,3 +120,13 @@ MIT License - Free for commercial and non-commercial use.
 
 - **Code:** [github.com/TrevTron/rtl-ml](https://github.com/TrevTron/rtl-ml)
 - **Blog:** RTL-SDR.com article (coming soon)
+- **Hardware Guide:** [Indiedroid Nova Setup](https://github.com/TrevTron/rtl-ml/blob/main/docs/HARDWARE_SETUP.md)
+
+## Contributions
+
+Captured in Temecula, CA (Southern California) using:
+- Clear line of sight to multiple signal sources
+- Validated with spectral analysis and manual inspection
+- All samples meet minimum SNR requirements (>10 dB for modulated signals)
+
+For questions or improvements, see the [GitHub repository](https://github.com/TrevTron/rtl-ml).