X                   | y
feature1  feature2  | label
--------------------+------
0.1       0.3       | 0
0.2       0.1       | 1
0.7       0.5       | 1
0.8       0.3       | 1
0.6       0.6       | 1 (but also 0 - so probably should be 0 and 1 - class 2?)
0.3       0.9       | 0
0.5       0.5       | 0 (but also 1 - so probably should be both as well- class 2?)

X                   | Y
feature1  feature2  | class0?  class1?
--------------------+-----------------
0.1       0.3       | 1        0
0.2       0.1       | 0        1
0.7       0.5       | 0        1
0.8       0.3       | 0        1
0.6       0.6       | 1        1
0.3       0.9       | 1        0
0.5       0.5       | 1        1

import numpy as np
from sklearn.ensemble import RandomForestClassifier

X = np.random.random((3, 3))
Y = np.array([[0, 1],
              [1, 0],
              [1, 1]])
model = RandomForestClassifier()
model.fit(X, Y)
model.predict(X)

    np.array([[0., 1.],
              [1., 0.],
              [1., 1.]])

model.predict_proba(X)

    [np.array([[0.6, 0.4],
               [0.7, 0.3],
               [0.1, 0.9]]),
     np.array([[0.9, 0.1],
               [1.,  0. ],
               [0.2, 0.8]])]