import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import xgboost as xgb
from sklearn.model_selection import KFold
from sklearn.neural_network import MLPClassifier

"""
    Station multi classification.
"""


def run():
    """
    neural network model
    """
    mlpc = MLPClassifier(
        hidden_layer_sizes=(100,),
        activation='relu',
        solver='adam',
        alpha=0.0001,
        batch_size='auto',
        learning_rate='constant',
        learning_rate_init=0.001,
        power_t=0.5,
        max_iter=200,
        shuffle=True,
        random_state=None,
        tol=0.0001,
        verbose=False,
        warm_start=False,
        momentum=0.9,
        nesterovs_momentum=True,
        early_stopping=False,
        validation_fraction=0.1,
        beta_1=0.1,
        beta_2=0.999,
        epsilon=1e-08
    )


if __name__ == "__main__":
    run()
