MLPClassifier.py

import numpy as np
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.datasets import load_iris
from sklearn.neural_network import MLPClassifier

iris_dataset = load_iris()
data = pd.DataFrame(iris_dataset.data, columns=iris_dataset.feature_names)
data['target'] = iris_dataset.target

validation = data.sample(5)
data.drop(validation.index, axis=0, inplace=True)

features = data.drop('target', axis=1)
x_train, x_test, y_train, y_test = train_test_split(features, data['target'], random_state=42, test_size=0.25)

model = MLPClassifier(max_iter=1000)
model.fit(x_train, y_train)