基于传统机器学习DNN算法的恶意网站检测python源码+数据集.zip

#可视化展示数据 import matplotlib.pyplot as plt import pandas as pd f = pd.read_excel("D:/创新设计/vic(1).xlsx") d = pd.read_excel('D:/创新设计/vic(2).xlsx') list1 = f['length'] dist1 = d['length'] x1_data = [] data_dict = {} for key in list1: data_dict[key] = data_dict.get(key,0) + 1 for i in list1: if not i in x1_data: x1_data.append(i) x1_data.sort() y1_data = [] for i in x1_data: y1_data.append(data_dict[i]) a1_data = [] data_dict = {} for key in dist1: data_dict[key] = data_dict.get(key,0) + 1 for i in dist1: if not i in a1_data: a1_data.append(i) a1_data.sort() b1_data = [] for i in a1_data: b1_data.append(data_dict[i]) list2 = f['split'] dist2 = d['split'] x2_data = [] data_dict = {} for key in list2: data_dict[key] = data_dict.get(key,0) + 1 for i in list2: if not i in x2_data: x2_data.append(i) x2_data.sort() y2_data = [] for i in x2_data: y2_data.append(data_dict[i]) a2_data = [] data_dict = {} for key in dist2: data_dict[key] = data_dict.get(key,0) + 1 for i in dist2: if not i in a2_data: a2_data.append(i) a2_data.sort() b2_data = [] for i in a2_data: b2_data.append(data_dict[i]) list3 = f['special'] dist3 = d['special'] x3_data = [] data_dict = {} for key in list3: data_dict[key] = data_dict.get(key,0) + 1 for i in list3: if not i in x3_data: x3_data.append(i) x3_data.sort() y3_data = [] for i in x3_data: y3_data.append(data_dict[i]) a3_data = [] data_dict = {} for key in dist3: data_dict[key] = data_dict.get(key,0) + 1 for i in dist3: if not i in a3_data: a3_data.append(i) a3_data.sort() b3_data = [] for i in a3_data: b3_data.append(data_dict[i]) list4 = f['rate'] dist4 = d['rate'] x4_data = [] data_dict = {} for key in list4: data_dict[key] = data_dict.get(key,0) + 1 for i in list4: if not i in x4_data: x4_data.append(i) x4_data.sort() y4_data = [] for i in x4_data: y4_data.append(data_dict[i]) a4_data = [] data_dict = {} for key in dist4: data_dict[key] = data_dict.get(key,0) + 1 for i in dist4: if not i in a4_data: a4_data.append(i) a4_data.sort() b4_data = [] for i in a4_data: b4_data.append(data_dict[i]) list5 = f['max_num'] dist5 = d['max_num'] x5_data = [] data_dict = {} for key in list5: data_dict[key] = data_dict.get(key,0) + 1 for i in list5: if not i in x5_data: x5_data.append(i) x5_data.sort() y5_data = [] for i in x5_data: y5_data.append(data_dict[i]) a5_data = [] data_dict = {} for key in dist5: data_dict[key] = data_dict.get(key,0) + 1 for i in dist5: if not i in a5_data: a5_data.append(i) a5_data.sort() b5_data = [] for i in a5_data: b5_data.append(data_dict[i]) list6 = f['change'] dist6 = d['change'] x6_data = [] data_dict = {} for key in list6: data_dict[key] = data_dict.get(key,0) + 1 for i in list6: if not i in x6_data: x6_data.append(i) x6_data.sort() y6_data = [] for i in x6_data: y6_data.append(data_dict[i]) a6_data = [] data_dict = {} for key in dist6: data_dict[key] = data_dict.get(key,0) + 1 for i in dist6: if not i in a6_data: a6_data.append(i) a6_data.sort() b6_data = [] for i in a6_data: b6_data.append(data_dict[i]) plt.subplot(2,2,1) plt.plot(x1_data,y1_data, '-', color = 'red',linewidth = 1,label = 'black_list') plt.plot(a1_data,b1_data,'-',color = 'green',linewidth=1,label='white_list') plt.title('length') plt.legend() plt.xlabel('x1') plt.ylabel('y1') plt.subplot(2,2,2) plt.plot(x2_data,y2_data, '-', color = 'red',linewidth = 1,label = 'black_list') plt.plot(a2_data,b2_data,'-',color = 'green',linewidth=1,label='white_list') plt.title('split') plt.legend() plt.xlabel('x2') plt.ylabel('y2') plt.subplot(2,2,3) plt.plot(x3_data,y3_data, '-', color = 'red',linewidth = 1,label = 'black_list') plt.plot(a3_data,b3_data,'-',color = 'green',linewidth=1,label='white_list') plt.title('special') plt.legend() plt.xlabel('x3') plt.ylabel('y3') plt.subplot(2,2,4) plt.plot(x4_data,y4_data, '-', color = 'red',linewidth = 1,label = 'black_list') plt.plot(a4_data,b4_data,'-',color = 'green',linewidth=1,label='white_list') plt.title('rate') plt.legend() plt.xlabel('x4') plt.ylabel('y4') plt.show() plt.subplot(2,2,1) plt.plot(x5_data,y5_data, '-', color = 'red',linewidth = 1,label = 'black_list') plt.plot(a5_data,b5_data,'-',color = 'green',linewidth=1,label='white_list') plt.title('max_num') plt.legend() plt.xlabel('x5') plt.ylabel('y5') plt.subplot(2,2,2) plt.plot(x6_data,y6_data, '-', color = 'red',linewidth = 1,label = 'black_list') plt.plot(a6_data,b6_data,'-',color = 'green',linewidth=1,label='white_list') plt.title('change') plt.legend() plt.xlabel('x6') plt.ylabel('y6') plt.show()