import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
# 读取数据
data = pd.read_csv('water_quality_data.csv')
# 数据清洗和处理
data.dropna(inplace=True)
features = data.drop('label', axis=1)
labels = data['label']
# 划分训练集和测试集
X_train, X_test, y_train, y_test = train_test_split(features, labels, test_size=0.2, random_state=42)
# 特征标准化
scaler = StandardScaler()
X_train_scaled = scaler.fit_transform(X_train)
X_test_scaled = scaler.transform(X_test)
海思平台-基于机器视觉的水质检测与预测技术.zip
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2023-11-06
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