def jeremy_trick_RF_sample_size(n):
if LooseVersion(sklearn.__version__) >= LooseVersion("0.24"):
forest._generate_sample_indices = \
(lambda rs, n_samples, _:
forest.check_random_state(rs).randint(0, n_samples, n))
else:
forest._generate_sample_indices = \
(lambda rs, n_samples: forest.check_random_state(rs).randint(0, n_samples, n))
def set_rf_samples(n):
""" Changes Scikit learn's random forests to give each tree a random sample of
n random rows.
"""
_forest._generate_sample_indices = (
lambda rs, n_samples, n_samples_bootstrap: _forest.check_random_state(
rs).randint(0, n_samples, n))
def jeremy_trick_reset_RF_sample_size():
forest._generate_sample_indices = (
lambda rs, n_samples: forest.check_random_state(rs).randint(
0, n_samples, n_samples))
def reset_rf_samples():
""" Undoes the changes produced by set_rf_samples.
"""
_forest._generate_sample_indices = lambda rs, n_samples: _forest.check_random_state(
rs).randint(0, n_samples, n_samples)