How to visualize multi-instance multiclass classification?
You could use a 3d-scatter plot, where each class would correspond to one axis and the color-intensity of the point would indicate the score value(e.g. for a grayscale colormap, the whiter the closer to 1 the value of the score).

Using the above format:

from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import pandas as pd


df = pd.DataFrame([[0.529, 5.0, 7.0, 4.0], [0, 3.0, 4.0, 2.0], [0.774, 10.0, 7.0, 6.0], [0.774, 10.0, 8.0, 5.0], [1, 3.0, 0.0, 2.0]])
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.scatter(df[1].values, df[2].values, df[3].values, c=df[0].values, cmap='gray', s=50, vmin=0.,vmax=1)

ax.set_xlabel('X Label')
ax.set_ylabel('Y Label')
ax.set_zlabel('Z Label')

plt.show()



You can change the scatter plot attributes for marker-size, colormap etc. according to the documentation to match your tastes.