写一个人工智能代码
// Import necessary libraries
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
from sklearn.neural_network import MLPClassifier
// Load the data set
data = pd.read_csv("dataSet.csv")
// Split the dataset into training and testing data sets
X = data.iloc[:, 0:4] # Independent Variables Y = data['target'] # Dependent Variable X_train, X_test, y_train, y_test = train_test_split(X, Y, test_size=0.2)
// Scale the data set for better performance scaler = StandardScaler() scaler.fit(X) X = scaler.transform(X) X_train, X_test, y_train, y
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