基于决策树的旋转机械故障诊断（Python）

最新推荐文章于 2025-06-14 23:46:26 发布

哥廷根数学学派

最新推荐文章于 2025-06-14 23:46:26 发布

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分类专栏：故障诊断信号处理机器学习文章标签：决策树 python 算法人工智能开发语言机器学习

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前置文章：

将一维机械振动信号构造为训练集和测试集（Python）

https://mp.weixin.qq.com/s/DTKjBo6_WAQ7bUPZEdB1TA

旋转机械振动信号特征提取（Python）

https://mp.weixin.qq.com/s/VwvzTzE-pacxqb9rs8hEVw

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from matplotlib.colors import ListedColormap
import matplotlib.patches as mpatches
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import MinMaxScaler
from sklearn.neighbors import KNeighborsClassifier
from sklearn.metrics import classification_report
from sklearn.metrics import confusion_matrix
from sklearn import tree
import joblib

df_train = pd.read_csv("statistics_10_train.csv" , sep = ',')
df_test = pd.read_csv("statistics_10_test.csv" , sep = ',')

X_train = df_train[['Kurtosis', 'Impulse factor', 'RMS', 'Margin factor', 'Skewness',
               'Shape factor', 'Peak to peak', 'Crest factor']].values
y_train = df_train['Tipo'].values
X_test = df_test[['Kurtosis', 'Impulse factor', 'RMS', 'Margin factor', 'Skewness',
               'Shape factor', 'Peak to peak', 'Crest factor']].va