Trained Random Forest Model for PNW Seismic Event Classification Trained on 150s waveforms (P-50, P+100), 50 Hz, and 1-10 Hz BP Filtered

This dataset contains three trained random forest models named as following - P_10_100_F_1_10_50.joblib - This is a model trained on 110s long waveforms (origin time - 10, origin time +100) in case of earthquakes and explosions and (first arrival pick -10, first arrival pick + 100) in case of surface events, the waveforms are tapered using 10% cosine taper, bandpass filtered between 1-10 Hz using Butterworth four corner filter, normalized and resampled to 50 Hz. P_50_100_F_1_10_50.joblib P_10_30_F_1_15_50.joblib. And also the standard scaler parameters for each features that will be used to normalize them.