Scott

Results 2 issues of Scott

**Code taken from:** https://github.com/tensorflow/probability/blob/main/tensorflow_probability/examples/jupyter_notebooks/Modeling_with_JointDistribution.ipynb **Code to reproduce:** dfhogg = pd.DataFrame(np.array([[1,201,592,61,9,-0.84], [2,244,401,25,4,0.31], [3,47,583,38,11,0.64], [4,287,402,15,7,-0.27], [5,203,495,21,5,-0.33], [6,58,173,15,9,0.67], [7,210,479,27,4,-0.02], [8,202,504,14,4,-0.05], [9,198,510,30,11,-0.84], [10,158,416,16,7,-0.69], [11,165,393,14,5,0.30], [12,201,442,25,5,-0.46], [13,157,317,52,5,-0.03], [14,131,311,16,6,0.50], [15,166,400,34,6,0.73], [16,160,337,31,5,-0.52], [17,186,423,42,9,0.90], [18,125,334,26,8,0.40], [19,218,533,16,6,-0.78], [20,146,344,22,5,-0.56]]), columns=['id','x','y','sigma_y','sigma_x','rho_xy'])...

# Background I have pre-existing models trained on both public and private patient EEGs, unrelated to the Harvard Harmful Brain Activity Classification Contest sets. My intention is to directly make...