Untitled.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1\n"
     ]
    }
   ],
   "source": [
    "print(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import svm\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import csv\n",
    "\n",
    "def c_in(rowx,rowy,list,y):\n",
    "    y.append(rowy)\n",
    "    list.append(rowx)\n",
    "def prediction(clf,list):\n",
    "    res = clf.predict([list])\n",
    "    return res[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<csv.DictReader object at 0x000001EEF69C9940>\n"
     ]
    }
   ],
   "source": [
    "with open(\"G:\\\\untitled1\\\\venv\\\\Include\\\\xs\\\\csv_0.csv\") as f:\n",
    "    with open(\"G:\\\\untitled1\\\\venv\\\\Include\\\\xs\\\\csv_1.csv\") as f1:\n",
    "        f_csv = csv.DictReader(f)\n",
    "        f1_csv = csv.DictReader(f1)\n",
    "        print(f_csv)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<csv.DictReader object at 0x000001EEFF228F28>\n",
      "app------------------\n",
      "app------------------\n"
     ]
    }
   ],
   "source": [
    "with open(\"G:\\\\untitled1\\\\venv\\\\Include\\\\xs\\\\csv_0.csv\") as f:\n",
    "    with open(\"G:\\\\untitled1\\\\venv\\\\Include\\\\xs\\\\csv_1.csv\") as f1:\n",
    "        f_csv = csv.DictReader(f)\n",
    "        f1_csv = csv.DictReader(f1)\n",
    "        print(f_csv)\n",
    "        x = []\n",
    "        y = []\n",
    "        sign=0\n",
    "        for (row,row1) in zip(f_csv,f1_csv):\n",
    "            if sign==50000:\n",
    "                break\n",
    "            list = []\n",
    "            c_in(row['app'],row['is_attributed'],list,y)\n",
    "            x.append(list)\n",
    "            list = []\n",
    "            c_in(row1['app'],row1['is_attributed'],list,y)\n",
    "            x.append(list)\n",
    "            sign+=1\n",
    "        print(\"app------------------\")\n",
    "        clfapp = svm.SVC()  ##默认参数：kernel='rbf'\n",
    "        clfapp.fit(x, y)\n",
    "        print(\"app------------------\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<csv.DictReader object at 0x000001EEFFF11DD8>\n",
      "ip------------------\n",
      "ip------------------\n"
     ]
    }
   ],
   "source": [
    "with open(\"G:\\\\untitled1\\\\venv\\\\Include\\\\xs\\\\csv_0.csv\") as f:\n",
    "    with open(\"G:\\\\untitled1\\\\venv\\\\Include\\\\xs\\\\csv_1.csv\") as f1:\n",
    "        f_csv = csv.DictReader(f)\n",
    "        f1_csv = csv.DictReader(f1)\n",
    "        print(f_csv)\n",
    "        x = []\n",
    "        y = []\n",
    "        sign=0\n",
    "        for (row,row1) in zip(f_csv,f1_csv):\n",
    "            if sign==50000:\n",
    "                break\n",
    "            list = []\n",
    "            c_in(row['ip'],row['is_attributed'],list,y)\n",
    "            x.append(list)\n",
    "            list = []\n",
    "            c_in(row1['ip'],row1['is_attributed'],list,y)\n",
    "            x.append(list)\n",
    "            sign+=1\n",
    "        print(\"ip------------------\")\n",
    "        clfip = svm.SVC()  ##默认参数：kernel='rbf'\n",
    "        clfip.fit(x, y)\n",
    "        print(\"ip------------------\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<csv.DictReader object at 0x000001EE8FAD7D30>\n",
      "device------------------\n",
      "device------------------\n"
     ]
    }
   ],
   "source": [
    "with open(\"G:\\\\untitled1\\\\venv\\\\Include\\\\xs\\\\csv_0.csv\") as f:\n",
    "    with open(\"G:\\\\untitled1\\\\venv\\\\Include\\\\xs\\\\csv_1.csv\") as f1:\n",
    "        f_csv = csv.DictReader(f)\n",
    "        f1_csv = csv.DictReader(f1)\n",
    "        print(f_csv)\n",
    "        x = []\n",
    "        y = []\n",
    "        sign=0\n",
    "        for (row,row1) in zip(f_csv,f1_csv):\n",
    "            if sign==50000:\n",
    "                break\n",
    "            list = []\n",
    "            c_in(row['device'],row['is_attributed'],list,y)\n",
    "            x.append(list)\n",
    "            list = []\n",
    "            c_in(row1['device'],row1['is_attributed'],list,y)\n",
    "            x.append(list)\n",
    "            sign+=1\n",
    "        print(\"device------------------\")\n",
    "        clfdevice = svm.SVC()  ##默认参数：kernel='rbf'\n",
    "        clfdevice.fit(x, y)\n",
    "        print(\"device------------------\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<csv.DictReader object at 0x000001EE8178F7F0>\n",
      "os------------------\n",
      "os------------------\n"
     ]
    }
   ],
   "source": [
    "with open(\"G:\\\\untitled1\\\\venv\\\\Include\\\\xs\\\\csv_0.csv\") as f:\n",
    "    with open(\"G:\\\\untitled1\\\\venv\\\\Include\\\\xs\\\\csv_1.csv\") as f1:\n",
    "        f_csv = csv.DictReader(f)\n",
    "        f1_csv = csv.DictReader(f1)\n",
    "        print(f_csv)\n",
    "        x = []\n",
    "        y = []\n",
    "        sign = 0\n",
    "        for (row, row1) in zip(f_csv, f1_csv):\n",
    "            if sign == 50000:\n",
    "                break\n",
    "            list = []\n",
    "            c_in(row['os'], row['is_attributed'], list, y)\n",
    "            x.append(list)\n",
    "            list = []\n",
    "            c_in(row1['os'], row1['is_attributed'], list, y)\n",
    "            x.append(list)\n",
    "            sign += 1\n",
    "        print(\"os------------------\")\n",
    "        clfos = svm.SVC()  ##默认参数：kernel='rbf'\n",
    "        clfos.fit(x, y)\n",
    "        print(\"os------------------\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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