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)