MetaOptimization.meta_opt()

Complexity

Conditions

1

Size

Total Lines	33
Code Lines	23

Duplication

Lines	33
Ratio	100 %

Importance

Changes

0

import numpy as np
def meta_opt(para, X, y):

This code seems to be duplicated in your project.

    def model(para, X, y):
        model = DecisionTreeClassifier(
            max_depth=para["max_depth"],
            min_samples_split=para["min_samples_split"],
            min_samples_leaf=para["min_samples_leaf"],
        )
        scores = cross_val_score(model, X, y, cv=3)

        return scores.mean()

    search_config = {
        model: {
            "max_depth": range(2, 50),
            "min_samples_split": range(2, 50),
            "min_samples_leaf": range(1, 50),
        }
    }

    opt = Hyperactive(
        search_config,
        optimizer={
            "ParticleSwarm": {
                "inertia": para["inertia"],
                "cognitive_weight": para["cognitive_weight"],
                "social_weight": para["social_weight"],
            }
        },
        verbosity=None,
    )
    opt.search(X, y)

    return opt.score_best