Source code for chembee.config.benchmark.random_forest

from chembee.config.benchmark.BenchmarkAlgorithm import BenchmarkAlgorithm
from sklearn.ensemble import RandomForestClassifier
import os
import sys

sys.path.insert(0, os.path.abspath(
    os.path.join(os.path.dirname(__file__), "..")))


class RandomForestClassifier(BenchmarkAlgorithm):

    name = "random-forest"

    algorithms = (
        RandomForestClassifier(
            n_estimators=100,
            criterion="gini",
            max_depth=None,
            min_samples_split=2,
            min_samples_leaf=1,
            min_weight_fraction_leaf=0.0,
            max_features="sqrt",
            max_leaf_nodes=None,
            min_impurity_decrease=0.0,
            bootstrap=True,
            oob_score=False,
            n_jobs=None,
            random_state=None,
            verbose=0,
            warm_start=False,
            class_weight=None,
            ccp_alpha=0.0,
            max_samples=None,
        ),
        RandomForestClassifier(
            n_estimators=100,
            criterion="entropy",
            max_depth=None,
            min_samples_split=2,
            min_samples_leaf=1,
            min_weight_fraction_leaf=0.0,
            max_features="sqrt",
            max_leaf_nodes=None,
            min_impurity_decrease=0.0,
            bootstrap=True,
            oob_score=False,
            n_jobs=None,
            random_state=None,
            verbose=0,
            warm_start=False,
            class_weight=None,
            ccp_alpha=0.0,
            max_samples=None,
        ),
        RandomForestClassifier(
            n_estimators=100,
            criterion="log_loss",
            max_depth=None,
            min_samples_split=2,
            min_samples_leaf=1,
            min_weight_fraction_leaf=0.0,
            max_features="sqrt",
            max_leaf_nodes=None,
            min_impurity_decrease=0.0,
            bootstrap=True,
            oob_score=False,
            n_jobs=None,
            random_state=None,
            verbose=0,
            warm_start=False,
            class_weight=None,
            ccp_alpha=0.0,
            max_samples=None,
        ),
    )

    titles = (
        "Gini coefficient loss",
        "Shannon entropy loss",
        "Shannon log-loss",
    )