未命名文章

import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False

x = ['小米', '张三', '李四', '王五']
math = [88, 85, 92, 70]
english = [95, 75, 88, 82]

plt.figure(figsize=(10, 6))

plt.plot(x, math, marker='o', linestyle='-', color='purple', linewidth=2, label='数学')
plt.plot(x, english, marker='s', linestyle='--', color='yellow', linewidth=2, label='英语')

plt.title('学生成绩折线图', fontsize=18, fontweight='bold')
plt.xlabel('学生', fontsize=14)
plt.ylabel('成绩', fontsize=14)

plt.legend(fontsize=12, loc='upper right')

plt.ylim(68, 97)

plt.tight_layout()
plt.show()


from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
import numpy as np

iris = load_iris()
sample_count = len(iris.data)
feature_count = iris.data.shape[1]
class_names = iris.target_names
feature_names = iris.feature_names

X_train, X_test, y_train, y_test = train_test_split(
    iris.data, iris.target, test_size=0.4, random_state=42
)
train_size = len(X_train)
test_size = len(X_test)

print("--- 鸢尾花数据集数据标准化 ---\n")
print("数据集信息：")
print(f"- 样本数量：{sample_count}")
print(f"- 特征数量：{feature_count}")
print(f"- 类别名称：{class_names}")
print(f"- 特征名称：{feature_names}")
print("\n数据标准化完成：")
print(f"训练集大小：{train_size} 个样本")
print(f"测试集大小：{test_size} 个样本")