classifiers.py 文件源码

def __init__(self, penalty='l2', dual=False, tol=1e-4, C=1.0,
                 fit_intercept=True, intercept_scaling=1, class_weight=None,
                 random_state=None, solver='liblinear', max_iter=100,
                 multi_class='ovr', verbose=0, warm_start=False, n_jobs=1):
        self.penalty = penalty
        self.dual = dual
        self.tol = tol
        self.C = C
        self.fit_intercept = fit_intercept
        self.intercept_scaling = intercept_scaling
        self.class_weight = class_weight
        self.random_state = random_state
        self.solver = solver
        self.max_iter = max_iter
        self.multi_class = multi_class
        self.verbose = verbose
        self.warm_start = warm_start
        self.n_jobs = n_jobs

        self.minmax_scaler = MinMaxScaler()
        self.dsapp_cutoff = CutOff()
        self.lr = LogisticRegression(penalty=penalty,
                                     dual=dual,
                                     tol=tol,
                                     C=C,
                                     fit_intercept=fit_intercept,
                                     intercept_scaling=intercept_scaling,
                                     class_weight=class_weight,
                                     random_state=random_state,
                                     solver=solver,
                                     max_iter=max_iter,
                                     multi_class=multi_class,
                                     verbose=verbose,
                                     warm_start=warm_start,
                                     n_jobs=n_jobs)

        self.pipeline = Pipeline([
            ('minmax_scaler', self.minmax_scaler),
            ('dsapp_cutoff', self.dsapp_cutoff),
            ('lr', self.lr)
        ])