RF_xyz.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "872b7057-df12-4336-b7a2-5537e8d92fd6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Jupyter environment detected. Enabling Open3D WebVisualizer.\n",
      "[Open3D INFO] WebRTC GUI backend enabled.\n",
      "[Open3D INFO] WebRTCWindowSystem: HTTP handshake server disabled.\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pylab as plt\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "import pandas as pd\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "import open3d as o3d    \n",
    "# import laspy\n",
    "\n",
    "def PCA(data, correlation=False, sort=True):\n",
    "    average_data = np.mean(data,axis=0)       #求 NX3 向量的均值\n",
    "    decentration_matrix = data - average_data   #去中心化\n",
    "    H = np.dot(decentration_matrix.T,decentration_matrix)  #求解协方差矩阵 H\n",
    "    eigenvectors,eigenvalues,eigenvectors_T = np.linalg.svd(H)    # SVD求解特征值、特征向量\n",
    "    # 屏蔽结束\n",
    "\n",
    "    if sort:\n",
    "        sort = eigenvalues.argsort()[::-1]      #降序排列\n",
    "        eigenvalues = eigenvalues[sort]         #索引\n",
    "        eigenvectors = eigenvectors[:, sort]\n",
    "\n",
    "    return eigenvalues, eigenvectors\n",
    "\n",
    "def collFeatures(pcd,length,size = 0.8):\n",
    "    pcd_tree = o3d.geometry.KDTreeFlann(pcd)  #set a kd tree for tha point cloud, make searching faster\n",
    "    normals = []\n",
    "    llambda = []\n",
    "    lp = []\n",
    "    lo = []\n",
    "    lc = []\n",
    "    non_idx = []\n",
    "    # print(point_cloud_o3d)  #geometry::PointCloud with 10000 points.\n",
    "    print(length) #10000\n",
    "    for i in range(length):\n",
    "        # search_knn_vector_3d， input[point，x]      returns [int, open3d.utility.IntVector, open3d.utility.DoubleVector]\n",
    "        [_, idx, _] = pcd_tree.search_radius_vector_3d(pcd.points[i], size)  \n",
    "        # asarray is the same as array  but asarray will save the memeory\n",
    "        k_nearest_point = np.asarray(pcd.points)[idx, :]  #find the surrounding points for each point, set them as a curve and use PCA to find the normal\n",
    "        lamb, v = PCA(k_nearest_point)\n",
    "        if len(k_nearest_point) == 1:\n",
    "            non_idx.append(i)  # record the index that has no knn point\n",
    "            p = 0\n",
    "            o = 0\n",
    "            c = 0\n",
    "        else:\n",
    "            p = (lamb[1]-lamb[2])/lamb[0] # calculate features based on eigenvalues\n",
    "            o = pow(lamb[0]*lamb[1]*lamb[2],1.0/3.0)\n",
    "            c = lamb[2]/sum(lamb)\n",
    "        normals.append(v[:, 1])\n",
    "        llambda.append(lamb)\n",
    "        lp.append(p)\n",
    "        lo.append(o)\n",
    "        lc.append(c)\n",
    "    return np.array(normals),np.array(llambda),np.array(lp).reshape(length,-1),np.array(lo).reshape(length,-1),np.array(lc).reshape(length,-1), np.array(non_idx)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "20472e06-e0c7-4cac-bdae-fc321a631a5c",
   "metadata": {},
   "source": [
    "# Data Load"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8fcf8de4-76b9-47ba-8c64-22c845216a9f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1     19125652\n",
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      "6       628964\n",
      "3       288073\n",
      "14      242680\n",
      "13       24642\n",
      "Name: cla, dtype: int64\n",
      "1     19125652\n",
      "5      7069941\n",
      "13     3682513\n",
      "2      3448050\n",
      "11     1979855\n",
      "3       288073\n",
      "14      242680\n",
      "Name: cla, dtype: int64\n",
      "0    19125652\n",
      "3     7069941\n",
      "1     3690730\n",
      "4     3682513\n",
      "5     1979855\n",
      "2      288073\n",
      "Name: cla, dtype: int64\n",
      "0    417962\n",
      "1    276623\n",
      "4    243566\n",
      "3     94132\n",
      "5     14055\n",
      "2      4101\n",
      "Name: cla, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "######################### using pandas for point reading ################\n",
    "lxyz = pd.read_csv('./data/training/labelledLocalCRS/DEBY_LOD2_4959323/DEBY_LOD2_4959323.xyz', sep=\" \", header=0)\n",
    "lxyz.columns = [\"x\", \"y\", \"z\", \"cla\"]\n",
    "print(lxyz.cla.value_counts())\n",
    "\n",
    "lxyz_test = pd.read_csv('./data/test/labelledLocalCRS/DEBY_LOD2_4959459/DEBY_LOD2_4959459.xyz', sep=\" \", header=0)\n",
    "lxyz_test.columns = [\"x\", \"y\", \"z\", \"cla\"]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a406247d-5646-49d0-ae2d-592c2bbc924d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1     36429131\n",
      "16     7566216\n",
      "11     7534665\n",
      "5      7056168\n",
      "2      6351914\n",
      "12     5938935\n",
      "15     3797046\n",
      "17     3600867\n",
      "7      1393392\n",
      "3       691885\n",
      "6       475590\n",
      "10      419409\n",
      "14      304608\n",
      "8       220774\n",
      "13       49393\n",
      "9        29398\n",
      "Name: cla, dtype: int64\n",
      "81859391\n",
      "1     19125652\n",
      "5      6440977\n",
      "2      3448050\n",
      "12     1979855\n",
      "16     1911652\n",
      "17     1746219\n",
      "6       628964\n",
      "3       288073\n",
      "14      242680\n",
      "13       24642\n",
      "Name: cla, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "lxyz_1 = pd.read_csv('./data/training/labelledLocalCRS/DEBY_LOD2_4906981/DEBY_LOD2_4906981.xyz', sep=\" \", header=0)\n",
    "lxyz_1.columns = [\"x\", \"y\", \"z\", \"cla\"]\n",
    "lxyz_2 = pd.read_csv('./data/training/labelledLocalCRS/DEBY_LOD2_4959322/DEBY_LOD2_4959322.xyz', sep=\" \", header=0)\n",
    "lxyz_2.columns = [\"x\", \"y\", \"z\", \"cla\"]\n",
    "lxyz_3 = pd.read_csv('./data/training/labelledLocalCRS/DEBY_LOD2_4959460/DEBY_LOD2_4959460.xyz', sep=\" \", header=0)\n",
    "lxyz_3.columns = [\"x\", \"y\", \"z\", \"cla\"]\n",
    "lxyz_4 = pd.read_csv('./data/training/labelledLocalCRS/DEBY_LOD2_4959462/DEBY_LOD2_4959462.xyz', sep=\" \", header=0)\n",
    "lxyz_4.columns = [\"x\", \"y\", \"z\", \"cla\"]\n",
    "lxyz = pd.concat([lxyz_1, lxyz_2, lxyz_3, lxyz_4], axis = 0)\n",
    "print(lxyz.cla.value_counts())\n",
    "print(len(lxyz))\n",
    "\n",
    "lxyz_test = pd.read_csv('./data/training/labelledLocalCRS/DEBY_LOD2_4959323/DEBY_LOD2_4959323.xyz', sep=\" \", header=0)\n",
    "lxyz_test.columns = [\"x\", \"y\", \"z\", \"cla\"]\n",
    "print(lxyz_test.cla.value_counts())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "649f1d5c-46b7-46e8-abf7-17bcb3445421",
   "metadata": {},
   "source": [
    "# Sample Points & Merge class"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f1fd86f5-5459-44bd-b41b-fb5d87038040",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1     40674984\n",
      "11    13473600\n",
      "13    11216476\n",
      "5      7531758\n",
      "2      6351914\n",
      "7      1393392\n",
      "3       691885\n",
      "14      304608\n",
      "8       220774\n",
      "Name: cla, dtype: int64\n",
      "0    40674984\n",
      "5    13473600\n",
      "4    11216476\n",
      "3     7531758\n",
      "1     6656522\n",
      "6     1393392\n",
      "2      691885\n",
      "7      220774\n",
      "Name: cla, dtype: int64\n",
      "0    19125652\n",
      "3     7069941\n",
      "1     3690730\n",
      "4     3682513\n",
      "5     1979855\n",
      "2      288073\n",
      "Name: cla, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "lclass = lxyz['cla'].replace({6:5,9:1,15:1,10:1,12:11,17:13,16:13})\n",
    "print(lclass.value_counts())\n",
    "lxyz = lxyz.drop('cla',axis = 1) #delete the column of class，the rest part can be viewed as the input 'features'\n",
    "lxyz = lxyz.to_numpy().reshape(-1,3)\n",
    "# lxyz = lxyz[0:300000]\n",
    "\n",
    "lclass_test = lxyz_test['cla'].replace({6:5,9:1,15:1,10:1,12:11,17:13,16:13})\n",
    "lxyz_test = lxyz_test.drop('cla',axis = 1)\n",
    "# lxyz_test = lxyz_test[0:100000]\n",
    "lxyz_test = lxyz_test.to_numpy().reshape(-1,3)\n",
    "\n",
    "lclass = lclass.replace({5:4,13:5,11:6,14:2})\n",
    "lclass_test = lclass_test.replace({5:4,13:5,11:6,14:2})\n",
    "\n",
    "lclass = lclass.replace({1:0,2:1,3:2,4:3,5:4,6:5,7:6,8:7})\n",
    "lclass_test = lclass_test.replace({1:0,2:1,3:2,4:3,5:4,6:5,7:6,8:7})\n",
    "print(lclass.value_counts())\n",
    "print(lclass_test.value_counts())\n",
    "# 0: wall\n",
    "# 1: window\n",
    "# 2: door\n",
    "# 3: molding\n",
    "# 4: other\n",
    "# 5: terrian\n",
    "# 7: column\n",
    "# 8: arch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d135c610-9720-41ec-bfaf-10a070c552d0",
   "metadata": {},
   "outputs": [],
   "source": [
    "######################### using open3d for point processing ################\n",
    "device = o3d.core.Device(\"CPU:0\")\n",
    "dtype = o3d.core.float32\n",
    "pcd = o3d.t.geometry.PointCloud(device)\n",
    "pcd.point.positions = o3d.core.Tensor(lxyz, dtype, device)\n",
    "pcd.point.labels = o3d.core.Tensor(lclass.to_numpy().reshape(-1,1), o3d.core.int32, device)\n",
    "# o3d.visualization.draw([pcd])\n",
    "downpcd = pcd.voxel_down_sample(voxel_size = 0.05)\n",
    "\n",
    "lxyz_train = downpcd.point.positions.numpy()\n",
    "lclass_train = downpcd.point.labels.numpy()\n",
    "\n",
    "pcd_train = o3d.geometry.PointCloud()\n",
    "pcd_train.points = o3d.utility.Vector3dVector(lxyz_train)\n",
    "\n",
    "# show in color\n",
    "colors = plt.get_cmap(\"tab20\")(np.array(lclass_train).reshape(-1) / 17.0)\n",
    "colors = colors[:,0:3]\n",
    "pcd_train.colors=o3d.utility.Vector3dVector(colors)\n",
    "# o3d.visualization.draw_geometries([pcd_train], window_name='test the color',width=800,height=600)\n",
    "\n",
    "\n",
    "pcd_test = o3d.t.geometry.PointCloud(device)\n",
    "pcd_test.point.positions = o3d.core.Tensor(lxyz_test, dtype, device)\n",
    "pcd_test.point.labels = o3d.core.Tensor(lclass_test.to_numpy().reshape(-1,1), o3d.core.int32, device)\n",
    "# o3d.visualization.draw([pcd])\n",
    "downpcd_test = pcd_test.voxel_down_sample(voxel_size = 0.05)\n",
    "\n",
    "lxyz_test = downpcd_test.point.positions.numpy()\n",
    "lclass_test = downpcd_test.point.labels.numpy()\n",
    "\n",
    "pcd_test = o3d.geometry.PointCloud()\n",
    "pcd_test.points = o3d.utility.Vector3dVector(lxyz_test)\n",
    "\n",
    "# show in color\n",
    "colors = plt.get_cmap(\"tab20\")(np.array(lclass_test).reshape(-1) / 17.0)\n",
    "colors = colors[:,0:3]\n",
    "pcd_test.colors=o3d.utility.Vector3dVector(colors)\n",
    "# o3d.visualization.draw_geometries([pcd_test], window_name='test the color',width=800,height=600)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "5ff6e4c7-0544-4522-a1fb-87aa6deac3eb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[-15.994701  -28.934046    7.604593 ]\n",
      " [-15.994704  -28.856184    7.1257396]\n",
      " [-15.994709  -28.87749     4.6099224]\n",
      " ...\n",
      " [  6.724885   -2.242188    0.2575329]\n",
      " [ -7.3672585  -2.274561   17.025852 ]\n",
      " [ -7.473833   -2.568303   16.997416 ]]\n"
     ]
    }
   ],
   "source": [
    "print(lxyz)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "83dc49b3-d6e6-4be4-b0ca-5fb1869819f3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[-16.        -28.95        7.6      ]\n",
      " [-16.        -28.9         7.1      ]\n",
      " [-16.        -28.9         4.6      ]\n",
      " ...\n",
      " [  6.7000003  -2.25        0.25     ]\n",
      " [ -7.4        -2.3        17.       ]\n",
      " [ -7.5        -2.6000001  16.95     ]]\n"
     ]
    }
   ],
   "source": [
    "print(lxyz_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "01b640ad-5b01-4497-8136-a9810e6ff1b7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[  0.6      -22.5        7.15    ]\n",
      " [  0.6      -22.300001  11.6     ]\n",
      " [  0.6      -22.5       11.45    ]\n",
      " ...\n",
      " [ 14.25      16.15      11.7     ]\n",
      " [ 14.2       16.1       11.650001]\n",
      " [ 14.2       16.15      11.650001]]\n"
     ]
    }
   ],
   "source": [
    "print(lxyz_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "7f330873-4d40-41f6-9835-4c9bb5ed9d4c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0]\n",
      " [0]\n",
      " [0]\n",
      " ...\n",
      " [4]\n",
      " [4]\n",
      " [4]]\n"
     ]
    }
   ],
   "source": [
    "print(lclass_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "25f5ec15-c806-4a45-a728-de61bde84035",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1]\n",
      " [1]\n",
      " [1]\n",
      " ...\n",
      " [4]\n",
      " [4]\n",
      " [4]]\n"
     ]
    }
   ],
   "source": [
    "print(lclass_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "994761d8-d658-4f8c-a91c-100f0644a3e9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "14623737\n"
     ]
    }
   ],
   "source": [
    "print(len(lxyz_train))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "30ea4064-6e2e-4cc4-9dcb-1f4adc212d60",
   "metadata": {},
   "source": [
    "# Classificatino based on RF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "ccff1067-d275-4c7b-97d0-2ecd96b9346b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(14623737, 3)\n",
      "(4222258, 3)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\15597\\AppData\\Local\\Temp\\ipykernel_16948\\2699409989.py:14: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
      "  rfc.fit(x_train,y_train) # model fitting\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.6726422212948616\n"
     ]
    }
   ],
   "source": [
    "######################### Classification based on RF #######################\n",
    "# divide the dataset into training and testing \n",
    "x_train = np.array(lxyz_train)\n",
    "y_train = np.array(lclass_train)\n",
    "x_test = np.array(lxyz_test)\n",
    "y_test = np.array(lclass_test)\n",
    "\n",
    "# x_train,x_test,y_train,y_test = train_test_split(lxyz,lclass[0:300000],test_size = 0.3,random_state=0)\n",
    "\n",
    "print(x_train.shape) #check the amount of dataset\n",
    "print(x_test.shape)\n",
    "\n",
    "rfc = RandomForestClassifier() # using the default parameters for RF to train\n",
    "rfc.fit(x_train,y_train) # model fitting\n",
    "\n",
    "# way to score your result\n",
    "score1 = rfc.score(x_test,y_test) #check the result that used in testing dataset\n",
    "print(score1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "143d5009-506b-4840-810c-fbf14fa7f517",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  Name of Feature  importance\n",
      "2               z    0.420046\n",
      "0               x    0.307654\n",
      "1               y    0.272300\n",
      "success!\n"
     ]
    }
   ],
   "source": [
    "importance = rfc.feature_importances_ # Check the importance of each feature\n",
    "col = ['x','y','z']\n",
    "\n",
    "re = pd.DataFrame({'Name of Feature':np.array(col),'importance':importance}).sort_values(by = 'importance',axis = 0,ascending = False)\n",
    "print(re)\n",
    "\n",
    "print(\"success!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "8e44d5ae-1c34-4969-b307-2e3b6c6b6b02",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred_rf = rfc.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "0b5c77b3-ed0e-4bea-9d17-38e9e0090b4d",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import confusion_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "7d1e4462-4756-4225-baeb-60e5bd7f3c3f",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 376,
     "status": "ok",
     "timestamp": 1674088910585,
     "user": {
      "displayName": "SUKIDA Tan",
      "userId": "04234593673225449814"
     },
     "user_tz": -60
    },
    "id": "LvqVmt0i2ds3",
    "outputId": "2f890904-33c1-49e0-c5a9-7ba544a7cef6"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.6726422212948616\n"
     ]
    }
   ],
   "source": [
    "cm = confusion_matrix(y_test, y_pred_rf);\n",
    "cm\n",
    "correct_rate = np.diagonal(cm).sum()/cm.sum()\n",
    "print(correct_rate)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "5c4bf118-ddc0-4d7e-b6e8-62bf742eb9da",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 245,
     "status": "ok",
     "timestamp": 1674086880589,
     "user": {
      "displayName": "SUKIDA Tan",
      "userId": "04234593673225449814"
     },
     "user_tz": -60
    },
    "id": "jQryCKH4R1FW",
    "outputId": "528acf69-4698-4cea-be2a-ded3b34f69d9"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'wall & balcony & ..': 0,\n",
       " 'window & blinds': 1,\n",
       " 'door': 2,\n",
       " 'molding & decoration': 3,\n",
       " 'ground surface & terrian': 4,\n",
       " 'roof & others': 5,\n",
       " 'column': 6,\n",
       " 'arch': 7}"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "classes = {'wall & balcony & ..': 0,\n",
    "           'window & blinds': 1,\n",
    "           'door': 2,\n",
    "           'molding & decoration': 3,\n",
    "           'ground surface & terrian': 4,\n",
    "           'roof & others': 5,\n",
    "           'column': 6,\n",
    "           'arch': 7\n",
    "           }\n",
    "cla_test = {'wall & balcony & ..': 0,\n",
    "           'window & blinds': 1,\n",
    "           'door': 2,\n",
    "           'molding & decoration': 3,\n",
    "           'ground surface & terrian': 4,\n",
    "           'roof & others': 5,\n",
    "           'column': 6,\n",
    "           'arch': 7}\n",
    "cla_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "9485e0ee-a8fb-4898-bb27-d4b3e12c3f93",
   "metadata": {
    "executionInfo": {
     "elapsed": 235,
     "status": "ok",
     "timestamp": 1674086267324,
     "user": {
      "displayName": "SUKIDA Tan",
      "userId": "04234593673225449814"
     },
     "user_tz": -60
    },
    "id": "MvIkJrRI2g8L"
   },
   "outputs": [],
   "source": [
    "import itertools\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# function from https://deeplizard.com/learn/video/0LhiS6yu2qQ\n",
    "def plot_confusion_matrix(cm, classes, normalize=False, title='Confusion matrix', cmap=plt.cm.Blues):\n",
    "    if normalize:\n",
    "        cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]\n",
    "        print(\"Normalized confusion matrix\")\n",
    "    else:\n",
    "        print('Confusion matrix, without normalization')\n",
    "\n",
    "    plt.imshow(cm, interpolation='nearest', cmap=cmap)\n",
    "    plt.title(title)\n",
    "    plt.colorbar()\n",
    "    tick_marks = np.arange(len(classes))\n",
    "    plt.xticks(tick_marks, classes, rotation=45)\n",
    "    plt.yticks(tick_marks, classes)\n",
    "\n",
    "    fmt = '.2f' if normalize else 'd'\n",
    "    thresh = cm.max() / 2.\n",
    "    for i, j in itertools.product(range(cm.shape[0]), range(cm.shape[1])):\n",
    "        plt.text(j, i, format(cm[i, j], fmt), horizontalalignment=\"center\", color=\"white\" if cm[i, j] > thresh else \"black\")\n",
    "\n",
    "    plt.tight_layout()\n",
    "    plt.ylabel('True label')\n",
    "    plt.xlabel('Predicted label')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "33e89c5c-9a91-4d7d-b601-d5d827077bff",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 652
    },
    "executionInfo": {
     "elapsed": 830,
     "status": "ok",
     "timestamp": 1674086917326,
     "user": {
      "displayName": "SUKIDA Tan",
      "userId": "04234593673225449814"
     },
     "user_tz": -60
    },
    "id": "YJeGeH212i6h",
    "outputId": "72dd3fa4-5411-44bb-c876-8f1e7cb6d839"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\15597\\AppData\\Local\\Temp\\ipykernel_16948\\1214108877.py:8: RuntimeWarning: invalid value encountered in true_divide\n",
      "  cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Normalized confusion matrix\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,8))\n",
    "plot_confusion_matrix(cm, list(cla_test.keys()), normalize=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "bef8ea5f-76f9-43ee-9c7f-a14a7c457aab",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 580
    },
    "executionInfo": {
     "elapsed": 1205,
     "status": "ok",
     "timestamp": 1674086946985,
     "user": {
      "displayName": "SUKIDA Tan",
      "userId": "04234593673225449814"
     },
     "user_tz": -60
    },
    "id": "9FeHmyzh2mZq",
    "outputId": "8cb5c54e-31e6-448c-c9c5-5b8b2c48c0bf"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Confusion matrix, without normalization\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,8))\n",
    "plot_confusion_matrix(cm, list(cla_test.keys()), normalize=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "b4645298-e415-4573-afb6-08e39988c833",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['rf_train_model_ld.m']"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import joblib\n",
    "joblib.dump(rfc, \"rf_train_model_ld.m\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0f1560cf-234d-4bb5-a7ca-0fbbef0c7db3",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "name": "python3"
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