59 lines
2.1 KiB
Python
59 lines
2.1 KiB
Python
# -*- coding: utf-8 -*-
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"""
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Created on Mon Oct 30 20:00:50 2017
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@author: wf
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"""
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import numpy as np
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import pandas as pd
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import matplotlib.pyplot as plt
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from sklearn import metrics
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from sklearn.svm import SVC
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from sklearn.model_selection import train_test_split
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from featurepossess import generate
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from sklearn.externals import joblib
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def test_c(flag,sql_flag):
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sql_dir = "./data/sql_test.csv"
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nor_dir = "./data/normal_test.csv"
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allm_dir = "./data/alltest_matrix.csv"
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if flag=='1' and sql_flag=='0':
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nor_matrix = generate(nor_dir, "./data/nor_matrix.csv", 0)
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return nor_matrix
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elif flag=='1' and sql_flag=='1':
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sql_matrix = generate(sql_dir, "./data/sqltest_matrix.csv", 1)
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return sql_matrix
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else:
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sql_matrix=generate(sql_dir,"./data/sqltest_matrix.csv",1)
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nor_matrix=generate(nor_dir,"./data/nortest_matrix.csv",0)
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df = pd.read_csv(sql_matrix)
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df.to_csv(allm_dir,encoding="utf_8_sig",index=False)
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df = pd.read_csv( nor_matrix)
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df.to_csv(allm_dir,encoding="utf_8_sig",index=False, header=False, mode='a+')
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return allm_dir
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def test_data(allm_dir):
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feature_max = pd.read_csv(allm_dir)
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arr=feature_max.values
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test_data = np.delete(arr, -1, axis=1) #删除最后一列
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#print(arr)
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test_target=arr[:,7]
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return test_data,test_target
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if __name__=="__main__":
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while(1):
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model_name=input("请输入要选择的模型名称：")
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clf = joblib.load('./file/'+model_name)
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print(model_name," has been loaded")
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flag=input("请输入测试文件个数：")
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sql_flag=input("请输入样本类型：")
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mode=test_c(flag,sql_flag)
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test_data,test_target=test_data(mode)
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y_pred=clf.predict(test_data)#预测
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print("y_pred:%s"%y_pred)
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print("test_target:%s"%test_target)
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#Verify
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print('Precision:%.3f' %metrics.precision_score(y_true=test_target,y_pred=y_pred))#查全率
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print('Recall:%.3f' %metrics.recall_score(y_true=test_target,y_pred=y_pred))#查准率
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print(metrics.confusion_matrix(y_true=test_target,y_pred=y_pred))#混淆矩阵
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