MachineLearning.py 文件源码

def ensemble(algs, alg_names, ensemble_name=None, in_ensemble=None, weights=None, voting="soft"):
    # Estimators for the ensemble
    estimators = []

    # Construct ensemble name
    if weights is not None:
        name = "Weighted Ensemble of "
    else:
        name = "Ensemble of "

    # Add respective algorithms to estimators and construct name
    for index, alg in enumerate(algs):
        if (in_ensemble is None) or in_ensemble[index]:
            estimators.append((alg_names[index], alg))
            name += alg_names[index] + ", "

    # Remove extra comma
    name = name[:-2]

    # Use provided name if not none
    if ensemble_name is not None:
        # Set name
        name = ensemble_name

    # Create ensemble
    alg = VotingClassifier(estimators=estimators, voting=voting, weights=weights)

    # Return ensemble and name
    return {"alg": alg, "name": name}