基于lightgbm的应用于充电桩的分类模型

 import lightgbm as lgb

    
 import pandas as pd
    
 import numpy as np
    
 from sklearn.model_selection import train_test_split
    
  
    
 #导入数据
    
 col_names = ['ID','K1K2驱动信号','电子锁驱动信号','急停信号','门禁信号',"THDV-M","THDI-M","label"]
    
 data = pd.read_csv(u'./datas/data_train.csv',names=col_names)
    
 # as_matrix()是将DataFrame的形式转换成数组
    
 dataset_X = data[["K1K2驱动信号","电子锁驱动信号","急停信号","门禁信号","THDV-M","THDI-M"]].as_matrix()
    
 dataset_Y = data[["label"]].values
    
 #将标签值转换成一维的一行y
    
 dataset_Y = np.array(dataset_Y).