in src/utils.py [0:0]
def _encode_target(y: np.ndarray):
# Encode the target column with the value 0 for the majority class and 1 for the minority class
y = y.reshape((-1, 1))
unique, counts = np.unique(y, return_counts=True)
assert len(unique) == 2
ret = np.zeros_like(y)
if counts[0] > counts[1]:
ret[y == unique[1]] = 1
else:
ret[y == unique[0]] = 1
assert np.sum(ret == 0) == max(counts)
assert np.sum(ret == 1) == min(counts)
return ret