使用萼蕊花数据集写一段DBN分类代码

以下是使用萼蕊花数据集写的DBN分类代码：

import numpy as np
from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
from sklearn.neural_network import BernoulliRBM
from sklearn.pipeline import Pipeline
from sklearn.linear_model import LogisticRegression

# 加载数据集
iris = load_iris()
X, y = iris.data, iris.target

# 数据预处理
scaler = StandardScaler()
X = scaler.fit_transform(X)

# 划分训练集和测试集
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)

# 定义 BernoulliRBM 模型
rbm = BernoulliRBM(n_components=2, learning_rate=0.01, n_iter=100, random_state=42)

# 定义逻辑回归模型
logistic = LogisticRegression(max_iter=1000, random_state=42)

# 定义 Pipeline
model = Pipeline(steps=[('rbm', rbm), ('logistic', logistic)])

# 训练模型
model.fit(X_train, y_train)

# 预测测试集
y_pred = model.predict(X_test)

# 输出准确率
accuracy = np.mean(y_pred == y_test)
print(f"准确率为：{accuracy}")

希望这段代码能够帮到你！