9，K-近邻算法（KNN）

导引：

如何进行电影分类

众所周知，电影可以按照题材分类，然而题材本身是如何定义的?由谁来判定某部电影属于哪 个题材?也就是说同一题材的电影具有哪些公共特征?这些都是在进行电影分类时必须要考虑的问 题。没有哪个电影人会说自己制作的电影和以前的某部电影类似，但我们确实知道每部电影在风格 上的确有可能会和同题材的电影相近。那么动作片具有哪些共有特征，使得动作片之间非常类似， 而与爱情片存在着明显的差别呢？动作片中也会存在接吻镜头，爱情片中也会存在打斗场景，我们 不能单纯依靠是否存在打斗或者亲吻来判断影片的类型。但是爱情片中的亲吻镜头更多，动作片中 的打斗场景也更频繁，基于此类场景在某部电影中出现的次数可以用来进行电影分类。

本章介绍第一个机器学习算法：K-近邻算法，它非常有效而且易于掌握。

1、k-近邻算法原理

简单地说，K-近邻算法采用测量不同特征值之间的距离方法进行分类。

• 优点：精度高(计算距离)、对异常值不敏感（单纯根据距离进行分类，会忽略特殊情况）、无数据输入假定（不会对数据预先进行判定）。
• 缺点：时间复杂度高、空间复杂度高。
• 适用数据范围：数值型和标称型。

工作原理

存在一个样本数据集合，也称作训练样本集，并且样本集中每个数据都存在标签，即我们知道样本集中每一数据 与所属分类的对应关系。输人没有标签的新数据后，将新数据的每个特征与样本集中数据对应的 特征进行比较，然后算法提取样本集中特征最相似数据（最近邻）的分类标签。一般来说，我们 只选择样本数据集中前K个最相似的数据，这就是K-近邻算法中K的出处,通常K是不大于20的整数。 最后 ，选择K个最相似数据中出现次数最多的分类，作为新数据的分类。

 

回到前面电影分类的例子，使用K-近邻算法分类爱情片和动作片。有人曾经统计过很多电影的打斗镜头和接吻镜头，下图显示了6部电影的打斗和接吻次数。假如有一部未看过的电影，如何确定它是爱情片还是动作片呢？我们可以使用K-近邻算法来解决这个问题。

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T423Kv6MsHsh9LL7103jHYRhttlPsuhcQB94XX1BHEWXfddc2fJg44ln30z0PTpk1tO278HT3YuzjA6MYB6mJcWLrxu+X3W4iyxAG/de4LARr4O3G+OMkMBr8htsk6XHTRRTlR7eKAc7CNMWyYY/bcc8+8c/D/0s+BmPPrOPLII22/EKJmk7k4YNiiT5N8wAEHhMUWW8z88aA8ZMgQezCRrqaVVAwqKw5q1aoVtt56a/suK664op0jbi4OeNiz3blz5/D111+H0aNHW5CjlU+rLUnr1q3teB7UHH/ttdeGtm3bFrw+Fwfcr0suucRe33XXXbYvKQ5o9SIMWDKbbh3OT2El+/fZZ5/w+++/5+4HrVYP3klcHNBif/bZZ/PMazi8m4RZLrlXDE3l87CTTjrJjvG/cY8ePWybYMd+WsZsY969UUgckJXYddddwxJLLBG++uor209KvU6dOjYT59yIgxNOOME+n3vP9i677GL7PSjzXSgAHT9+vH1e48aN7TfLe8i0sM3vF18aZYkDoEsgLg44lnvsJMUB/0/Y9gzNL7/8Ylm5pDggi+PifNq0aWHDDTe0z0HouDjYcsstLXsD/F2SWQshRM0kc3EwYMCAyBPC5MmTc2sueNDjgcTDlYxCluspJKmsOKhbt64V/E2ZMsWG2bkRUDhfXBxgb7zxhqWqMQ+uDzzwgB0Tx1t/V199de54AlIhXBwQRAmEtDYbNmxoLWruOV0gFKgxwuDCCy+0Y+MjLUipb7XVVub/+OOPc/ejIjUHaca94T44nTp1Mj9pc/8+n3zyifkI6kBtSf/+/e3z2U+r3M9XnjiAww47zLbPPPNM2/aun0L97mniALHqI0wQHOxHqEEyKHsxYTKA+nV410CSZFYpSZo4iE8CFr8O0v6MuKDGI97lxDkQRghDPwd/kwMPPDBnnqWhawFBxW+ZbcQu+/lb0b0lhBCZi4PzzjvPWsEY4iDZrUAAo3ix2FRWHJRXcxAXB2ynWZo4oDCMlHz8uIceeijaOycuDgg84OtTcN95wG+33XbWMgeCMfuSwzD9HHMrDvbaay8LyBijM/Btuumm0VGz6ghceKSZiwNghETaMRURB2RF2Oa78p357vHrSJImDjwoQ3niwFvsSXHg11GeOCBrk8bciIMHH3zQXpMdicM58Hfp0iV3jjTjO7ioIOvB35DMie8va/ZSIUTNIVNxwAOLVglFiYzr5iHKQw0frUggNer9uWQR6APlAVeoEK+qKIY4oGXGd3UjxU7goZWcBgWCtHo5lsBFkdidd94Z7c0nKQ5ILTNuHh/1CwTVrMRBvOaALgsmtiJzwTBBYKjgCiusYMfydydDQGbF7wOfRzC/4IILrLW7+uqrmx8ByXvi11GWOKD7Y+WVV7ZjvGaD71SIeRUHdI2xnRQHXCv+8sRB2rXdfPPNVvvhn1meOHjuuecsQ0RAj7fyKbbkmLg44PO4924MpUTMMWKCQliEGefAyFjxe11ooYXstRCiZlOl4oD0NostXXfddVbgxKgAUuNemMbsbRxD9wH9uIiBeN+w94MTMLJceAmyEgekxoGgQ/DxSYj4ngQwJkqiqyEJKV2KA/1+8JDnfJwjjaQ4AMTXzjvvbH6MYM35qEpnOy4O+LswEyX+eREHwMRWPu21j8bwboV4oR7X16FDB/uXbhn2Iwa9X9yDLFYRcQBU99MthZ9qe85diIqIA7olqJ/g7+ZBGdHCfUT0sE2dRrzLx0UZXWZpFBIHZFgI2OzzoYwe2KnP8N/CbbfdZr5kBiM+2oRuAX6bzNT5yiuvWL0H99brMTgvIp330a3gNQeIdb4L35f74ecQQtRsqlQc8GDmoUZgu/XWW8087YzRymMIlm9jPkSMgEkgoHCuGGQlDnyeA1qXbBOYKQbzYIildSvQcmSfB67KiAOHVrx/Fn8TZvnjNUPyfBbDF198MXdMXBwk09VxCokD8MBOgRvV/tQfEGjpH/c5Le677z47huvx+0Hg98I6PhsfVlFxAOzHH29tp1GeOADqFjiGbhpGU7jwIAXv4gCjK4zfDkWJ3h3EvAVpuDjYZJNNcv8vMP4e+Ckc9Hvk4gAjs8Jxvu3iACHJNsWtFEkyNJNiRC9IBB+ZgmjjHF4XQXcPWTkXBxj/Z11AkvETQohMuhVIm5M5IJ3NegM8+Nz23nvvsM0229hUuGzTaqGlw0P46KOPLlgpX9VURhzQyiP4pcHwPdKytF6BDAIjNfgM/mWIHVkDCsnSWre0sBnCx4gCqsq5HzzsKdhLoyxxEB8WyWeRqSGgkpFhil3OT0CldXn22Wdbi5kgx+gLhAX74+P6nbLEAS14rp39Hthp8dI10qRJEzsn+zkH10OGgcwGNScEMN/PPYifIykO+A633367bTsVFQcM0eT8Ppa/PHEAtMjZ5jjex2/Wh0syQgDBSLcKKfq0ewb8FhBJvMeNrgGuhfsRn7GRkSMnnnhi7jj+JhyHKHVxQHBHOODnvmG8pvbCQTRcc801lj3gPNxbsno+1wTn4LvQFcJ7sSOOOMIKWIUQIrOaA4oPeSgRDHnYua255prm96BMEKB/mpZ21nUGcSojDl566aXoVToElHh3CBmD3r17WyDg4c6aDuXBOXgP5kP+0qD1y/UTzJL4UEZagfGA5dkIN/rQ41AH4t0DCIYktFC5rkJrKHB/2B+fFIjhifj4/rTck1Bg59+X9SYgfo64OOBz7733Xnsdh/3028/tokqIg6SgQOTgd3FAhoPuAjI7PvcC1+HXjBW6H3EQFvH3+PwSaSCc/DivzUEYkeFJQkbDJ3VKg/vIecgUCSFERclMHPiYdVo4XvRE+thbeQRlgiWtbfqhvQ+X/lCK8ii8ypLKiIPKwsPe++KrCvqjEQ9payFwL7nf8X5xcL9bcj9wnezz/u6qgvOmfV55cC2F7h1i8qCDDrK/Y2UWYyp0TUk//fFeOyKEEDWBzMRBfMIbWj8UTzEqwYu3CMr0e9KvG6/e975r0rj0v2ZFMcWByAbPhNDnnzY1sxBCiMqRebcCmQLvF/Xq+EJBmcloPK1N98O4ceOiPVWPxMH8z+DBg21kTHzyJSGEEPNO5uJg1KhRuRX76Eagipr525NpWoY5MoMbfcxU8/vcB1khcSCEEEKkk4k4ILBTCU3wZciXiwOEAjMkUvAVXyMfYUDGgKI1iqeKgcSBEEIIkU4m4sADL8bwsbg4ePLJJ+01wwKBdQoY542PKvtiIXEghBBCpFPl4oApe5mClfHoTL7Cin2+qBDigCpwJm9h6Bnj/lnljiF3FCxWppq9skgcCCGEEOlUuThgDncKxVgdEBgfzkQ31BIwzS4wVp1JfjDGtlOfUGwkDoQQQoh0MitIjMMSwoXWui8VEgdCCCFEOkURB3HoOmCNhbKWIy4GEgdCCCFEOiURBwRlL0gsFRIHQgghRDoSBxIHQgghRB4SBxIHQgghRB6ZiQNmQEwbmliWOGBfZRfomVskDoQQQoh0MhMHzF2wyy672Jr+cWMGRIIysyQm9x133HG2r3v37tFZskPiQAghhEgnU3FA8F1rrbVs1by44a9Xr94c/tq1axddHDz66KORRwghhBCQuThgWeY4ZXUrLLnkkkUXB8zWKIQQQojZ1Hhx8MYbb0QeIYQQQkCNFwf7779/5BFCCCEEFF0cMJVydRIH6lYQQggh8slcHKy66qrhqKOOCg0bNgwHHnhgWH311c3Pyo3bb799aNu2bWjWrFno2LFjqFu3rsSBEEIIUWIyFwes0MjcBc8880z4/fffw8iRI82/yiqrhG+++SZ8//334dVXX7X34GPEQq9evWw7SyQOhBBCiHSqVc3BJ598Eq6//vpoK1skDoQQQoh0MhMHU6dOtawAWYM4ZYmDYiJxIIQQQqSTmTgohMSBEEIIUb2p8eLgnHPOiTxCCCGEgBovDu69997II0TpGDFiRGjRokVB69+/f3SkEEJkj7oV1K0gSgyLfzVv3tx+j4WMocCM/Pnvv/+idwkhRHaURBycdtpp4eqrr448xWfixIlh8803t4fuGWecEXmFKC7Tpk0LN9xwgwV+FwFNmjSx/x/bbbddzhe3P/74I3q3EEJkR9HFQXXgrbfeyj1stWSzKAWM5mHqbv8dMr9H165dw5dffmn7p0yZYpmCxo0b547BmCdECCGypujioF+/fpbS79atW+QpPhIHotQMGjQoL+gvtdRS0Z58jjvuuLzj2rdvH+0RQojsyEwc/Pnnn6FPnz5hyJAhkWcWxxxzjD3kTj311MgzCwI2x3/77beRJzskDkSp+eCDD2zacP8d7r333tGeOalVq1buOIkDIUQxyEwcTJ482R5mO+ywQ+SZhYuDZFA+++yzzT9s2LDIkx0SB6I6MHbsWPv9YXQzpHHFFVfkfqvYqFGjoj1CCJEdEgcSB6KaMn78+NCqVavcb7Vdu3bh77//jvYKIUR2ZCYOWIGRB5rEgRBzz5gxY2x+A/+dMqKhGP83hBACMhMHr7/+uj3UJA6EmDuou2nZsmXuN7rEEkuEAQMGRHuFECJ71K0gcSCqEQxlXHvttXO/T4zRPUIIUUwyEwfPPvusPdjWWWed8Nhjj+WsTZs25ucB6L5bb7011KtXz/wSB6Imw8yh/ttkeOPjjz9ukyUJIUQxyUwckCFo2rSpiYGhQ4fmbOedd7YH30YbbZTzMfdBgwYNzC9xIGoyq622Wu632bZt28grhBDFJTNxUIhC3QpkGhZZZBGJA1GjiYuDjz76KPIKIURxyUQcDB8+3LIGHTt2DNOnT4+8sygkDqBv375WiDVu3LjIkw0SB6K6Qn3BrrvuauZTKQshRLHJRBw89dRTFnipI/jqq68i7yzKEgePPvqo7evevXvkyQaJA1FdOeWUU2w+A2z06NGRVwghikum4uC8886LPLOROBCiMPFuhdatW0deIYQoLhIHEgeiGiFxIISoDtRIcTBixAhbIrfQdQhRKuLiYMstt4y8QghRXGqkOAAKvwpdhxClAnGAcN122201WkEIUTIyFQeNGjUK6623Xp4xsQv7GJWQ3LfSSitJHIgaDWsqfPzxxzbD6IwZMyKvEEIUl0zEwTfffBM22GADG47Vp0+fClv9+vUlDoQQQogSk4k4gP/++89sbnjkkUfCoosuGgYPHhx5skPiQAghhEgnM3FQGaZMmRLef//9aCtbJA6EEEKIdKqVOCgmEgdCCCFEOlUuDiimeumll6KtWbz++uvhwQcfNGPhJboOLr/88pwP22+//cxPtXYxkDgQQggh0qlyccB88Pfdd184+uijww477GC27rrrhhYtWpgtvvjiFpRZpvmFF17I2UknnRQWWmih0KxZs+hM2SJxIIQQQqSTWbcCQ7EIvgiC+BzxZc1zsOSSS0ocCCGEECUmM3Hwv//9L1x44YWWOYgTFwfnnHNOWHbZZa3bASQOhBBCiNKTaUHilVdeGZZZZpm8GoS4OGAFOl6//PLLtk/iQAghhCg9VS4OEAL9+/e314gDAnC/fv3CJZdcEiZNmiRxIIQQQlRzqlwc3HPPPbZgTPPmzUPDhg0tAPuUyaNGjZI4EEIIIao5mXQrTJw40WY7bN++vQXg0047zbZ//fVXiQMhhBCimpN5zQEBmHkMHIkDIYQQonojcSBxIIQQQuRRFHFw7733hpkzZ4bzzz8/rL322qFu3boWlE888UTbv/POO4enn346nHXWWWGVVVaJ3p0tEgdCCCFEOpmIgxdffNH+dXGAMUtiz549zQ8ffvhhbh8W31cMJA6EEEKIdKpcHDAtMnMbbLDBBmGFFVYI66yzTrjtttvChAkToiNm0a5dOwvOK620ksSBEEIIUY2ocnHwzjvvhCWWWMIC7y677GIjFJK8+uqroVGjRuHggw8Od999d6o4YPbEDz74INqqeiQOhBBCiHQy6VYgqCMSmEI5CcKgVq1aVm/AfhZpSooD3s8cCYMGDYo8VY/EgRBCCJFOpgWJcaZMmRKefPLJ0Lhx47DWWmvZ0s7g4oBixH///Tf8/ffftkIjPokDIYQQovgURRwgALbbbjsLxnQlxHFxgCEKOnbsmNuWOBBCCCGKT+bigFEKW2+9tYmCMWPGWGYgDtsXXXSR7Y/b5ZdfPsexVUlZ4mDgwIHhoYceSrXx48dHR4k4EllCCLHgkLk4YDnmH374IdqqPpQlDnwtCCZlWnnllW2dCLaxjTbaKDqqePz888/hq6++Cn/88YdtH3HEEWG33Xazrhr477//wo477piz7777zvxl0aFDh7D77rtHW/ncfPPNdh6Gm8Zh3Qz8++67b+SZzVZbbWXzWQghhJj/yVwcfPHFF6Fbt27RVj7UIFxwwQUW+IpNRcRB9+7dbXv69Ok2URO+RRdd1HzFpGvXrvbZZDSA+gy2O3XqZNv42V5uueUs4/LEE0+YvyxatmwZ6tevH23lw3k5H2tixOHviH/ppZeOPLMhQ8Q+IYQQ8z+ZP83XX399CxqIgDis0EhwYl8pWuPliQPmaJg2bVrkCdZqZ06GuDigxT548OA8Gz58eLS34nz99deWHXD4XM71119/2baLAz4f8P/444/h999/t23/Ls8995xtV4SKiAOOcb7//vuw2GKLmZ/RJizB7fTt2zfUrl07rLfeepGnesAwWu7jP//8E3mEEEJUhMzFQYsWLSygXHjhhZFnFvEZEm+88cbIWzw8oB5++OGRZzYVFQdcN+dYeOGFbRQG8zsQQEm/M0yT0Rd9+vQJe+211xyGH2666SYLqnGR4sGZzMXkyZPD6quvbtveYndx8Ntvv1kdh3d7uDiYMWOG7fduCOC78F3feOMN2ybwL7TQQrnriDNy5MhQp06dPHHAJFZ8BlNfL7LIImHVVVc1wcC02K1atbJ9iASgu+P666/P+74IHI6F9957L2+fG36uO+776aef7D3w559/2hTc8f0Y9wDIRMX9XgTLfXShJYQQonwyFQfUGxBoDzjggMgzGxcHzKBYym6FtNaudyu0adMmXHbZZWZt27Y1n4sDguXGG29svvPOO898fCcP1FOnTg3ffvutvcb2339/E0iHHXaYbXvKPi2D4UGNWSRp/VLQybaLA6anZhsR8dZbb9lrjNQ+3H///bbdo0cP2wbvEvCuCQK/nyMNPpvPczFx++232/GImf32289ejxs3zrpceN2kSROb2wI23XRT8zGRlQ9LxYYOHWr7+dd97Oc438bIMvmoFf4+XgTKol0NGjSw+4ideeaZdgz3C7i2+Dk4ZpNNNrFtumKEEEJUjEzEAQGPVqyvwMhD+ptvvglbbLFFGDBggB3DSo3so8CNY90efvhha6H7+gxZURFxQNaDaaB57ebiwIPyNttsE4YMGZK7fu97P+6448KkSZPCTjvtFDp37pxrxXtgp6iPboHyxAF4t0KaOKA1ftBBB9n2U089ZfubNm1q2/MiDpICY9ddd7VtRNHYsWPtNbUNLg4QBHDxxRdbdoFrJnvCiJNrrrnGsit+r10cnHDCCbaf7+DZEebAoLuGlv6RRx5pPv8tIEpYoMtBgLE/TRxwDiCL4ZkOIYQQFSMTceCBiCCx+OKLWyt58803N9+dd95px7Ru3doe2gQh0vMch9F3zXGFKumrivLEAYGYughS5wgaDNHC9fXr1y+vxZ5mhx56aHS2YK1vAji2/fbb544hfZ8mDph2Gl9FxAH4OUaMGGHb9erVs+15EQcM2+S7kpLnuy6//PKW/UAMEHB5L0E5KQ54jSW7irh2RAu4OCBj4HgXjXdNANeGz8UBQuLSSy/N3UsEFvvLEgdAbYXEgRBCVJxMxAEtWB7Qnm6HG264wXyIA2ZHJP3OkLkkHhjps86S8sRBs2bNoq3ZeFBG7Lg4oFvkjDPOmMMImoAw8LUmklZIHHz22WfmS4oD5n+AYogD8AwGAZt/OQfExQHZA16THQJeY1mIAzINfn4yM/4dJA6EEKJqKbo4oNCvS5culhkgLZzExcErr7wSebKhqsQBhW8+agDoHyc1/ssvv4TXXnstLLvssjZfAhmSTz75xGyPPfaw9xYSB4gAfElx4IG92OKArAFZIM/6UP2PAKKLxYWPT4fNa6yqxcG1115rBZR0TXEPySKQ2WG/xIEQQlQtRRMHPNApWsO/ww47WBU61fxYHBcHpe5WIPARSAmECJujjjrKro3ASxCmnoB6A85Bi5bjsHPPPdeCGMLH++mZsMgZPXp0WGWVVcyPOEBA+Dl8oSoPyklx8Mgjj9h2eeKARa3YnldxQPcJx2Ae2J2rr746t4+6ERd6XifQq1evXICmjgRxMS/iwIsWGZEA3CtqGfBJHAghRNVSNHFAy5KsAWPknVNOOcX6qunXd6qLOPAgEzfETbyFz7oQ2267bd4xrCb57LPP2v4rr7zSfAz16927txmZBD8WcUAQ82360TlmtdVWs+3K1hx4MSF98gz/4+/h2Yq5EQeMRuAYLCkOgHNQl+BFpoDYady4sb0HUcX38ZEeXodRGXHAdVOjwv3lnPx22IdJHAghRNWSqThgxj6m+mVYmhckxsXBVVddZdsM1WN8O1QHcUD6fMMNNzTj+l9++WV7TeBLQgaE8fkMq+MYD75AxT3V+34ujMBIloDXBF+CGK1sthEOCBNGciCsfPgd4ol9BGKCaFIcUDTItosDagK8WI9JqJZZZhk7P3MX+PWRvSHYMoqkEAgLplkmIHNNSTgHgTfJ888/Hxo1amSf78Z5GJYJ3AO+C+LB6d+/v11j/P6RneD3wfeFu+66y2o8OB+CizkaGGbK7JVANmfPPffMy1oAvz26f4QQQlSMTMUBD20PCGmZAyBAcWzPnj1tuzqIg1Lx6quvWmBNg4mVbr311vDmm2/OIQ4IhOxzgQXUPODDeC/w75dffmmvWX8hbQKkJLTuH3vssWgrn7LOwXfxz8cQGg4zQnr9Qnlw/vhaEUzmxPniE1S5eBBCCFE1FK1bAWjtVVQclNWirQqqozioKPS3k5UoxrTA1ITEW+FCCCEWfEouDigqo9+eyXXAxUG8DiEL5mdxIIQQQmRJycVBEokDIYQQorRkKg722WcfG8aGHX/88TbEryxxwFoEvoqjxIEQQghRGjIVB0zmw7A+zMfeJ8UBtQUUqGEMUeMYVg+MF7BlgcSBEEIIkU7RuhUYZsfwtqQ4YGw/x7ox4x5DB7NG4kAIIYRIJzNxwJh6H0LnMCfAxIkTo61ZzJgxw5Y6ZpIe7IUXXoj2ZIvEgRBCCJFOJuLghx9+yFtatzoicSCEEEKkk4k4mB+QOBBCCCHSyVQcUGDIIkNrr7125JkNhYgsXNS+ffvw888/R97iIXEghBBCpJOpOPCFh1jhMA2W/WW/L8hTTCQOhBBCiHSKIg7KWvSG6ZNZhdAZNGhQuP766/Pmzs8CiQMhhBAinaKIA1/R7/fff7cVCZkp0Y2hjaz1361bt3DzzTeHBg0a2HtYyTFLJA6EEEKIdKpcHLBIT79+/exfFwf333+/TYTEcrpHHnmkrci38sorW3cCrzGfNpkli9nm+CyROBBCCCHSqXJx8MQTT1igZ0bEfffd1wJw3Hyp3tatW4dDDjkkt7Lg2WefbfubNWtm21kjcSCEEEKkk0m3wi+//BLeeeedcPLJJ1sApq6AbYyJkABxwD6mScY6dOgQGjZsGB544AHbnzUSB0IIIUQ6Rak5SButEBcHn332mb3ef//9bVjjKaecYgIjSyQOhBBCiHSKIg4wsgcYqzPed999Nv8B/rvuuiv07NnTXm+yySZhww03tNcbb7yxzYWQFRIHQgghRDqZiIMff/zRllw+88wzc8KAxZTiRu0B+7CmTZvOsR+bPHlydMaqR+JACCGESCcTcbDVVluFli1b5oL/EUccEe2ZDYst+f746o3ASAUyClkicSCEEEKkk4k4YHVF5i5gHgMCsM9z8Nxzz4XHHnvM7JprrsmJg0suuSTn79u3b6hXr15YeOGFzZ8VEgdCCCFEOpmIg0mTJoXhw4fnag6Y3AjatGkTLrjggtCpU6ecMBg8eHC44447ctu1a9cOJ510Uhg2bJidIyskDoQQQoh0ilKQGB+t8L///c8mQ8K/22672TwHPloBQxgUA4kDIYQQIp2SiAMXAkyU9PTTT1tXAtu77767DW0sBhIHQgghRDpFFwdMqzxw4ECzXXfdNScUMDIKxVq+WeJACCGESKfo4sBhuOMWW2xh+9u3bx823XRTe73EEkuEHj162CJNWSJxIIQQQqSTiTh48cUXbSjj0ksvnScO3n777fDSSy/ZKITmzZvbvi5duoQZM2bYnAZMgoQP4xxZInEghBBCpJOJOPjuu+/CbbfdZsMRF1poodC5c+fw/PPPh+WXXz7Ur1/f7LLLLrN1FP7999/oXcFmRGRmRIL2PvvsE3mz4c0335Q4EEIIIVLItFuByYxuuummaKtiUHPAUMdff/018mSDF0ZKHIgs+OGHH8KoUaOiLSGEmL/IVByUBQ9OHqClQuJAZMno0aPDoEGDoi0hhJi/KJk4YFVGChL//vvvyFNcJA6EEEKIdIouDuLzHNDlwNDGUuAFiSNGjIg8QgghhIAqFwd9+vQJHTt2DJ988oltP/7442Hbbbe11+DigNEMpexWcHHACAohhBBCzKbKxQGjAJirgMWTKCzkdXyeA0YoEJSZA6GUSBwIIYQQ6WTSrbDCCivYHAfTp08PK6+8cp44OOaYYywop41iYCgjizQx1JGMQ5ZIHAghhBDpZCYOlllmGXvdokWLnDiggpu5DsgmsH/77bc3scACTLxm+mSEAUGbdRayROJACCGESKeo4sAnHho6dKiNVuA1Cy1Rk8Br5jigZkHiQAghhCgdRRUHrJ9www032OtC4uDbb7+VOBBCCCFKSFHEAVMoH3jggbYKI8GfzEHDhg1tyWamT5Y4EEIIIaoPRREHBOHTTjvNtsG7Dig+/Pjjj8NKK60UdtppJ1uA6dZbb5U4EEIIIUpI0cUB8xwstdRSYa211rJlme+77z7b37NnT9u/yy67SBwIIYQQJaTKxQGt/+WWWy5PHNStWzd8+OGH4Z9//gm9evWybbIHwBTKdDvceOONti1xIIQQleOvv/4q2pT0zG5LV/Bvv/0WeSoPsYHh7bfcckvkKT10efP9/vjjj8gzJwzX33///cNnn30WeSoP9+C6666z+8DrUlPl4uDiiy+2oOvigLqC5GiF4447zrZZxrl27dphtdVWs21wceCFi1khcSCEWNA48sgjw/Dhw6Ot2Xz11VeWncWmTJkSeecNhAjP0KZNm1rjb15477337FxHHXVU5Ck9zPLLNbH+zvjx4yNvPggjjtlqq60iT+V57bXX7FwY96PUVLk4mDx5cthyyy3D5ptvbtsoqzFjxoRXXnklbLbZZmH11Ve3aZOnTZsW9ttvv9C4ceMwbNgwOxZcHHz//feRJxskDoQQCxJXXHFFqFWrVu7Z63z99dcW4HjeEcjZrgrIHNx+++1hm222CU888UTkrRzVWRxgNGTTcHHAjMADBw6MvJVjgRcHMGHCBJvt0KHLgAwBdQbjxo2zdM0pp5xiN+HFF1+MjpqFxIEQQsw9nTt3tmfaKqusEnlC+Omnn8L6669v/sUXXzy8++670Z7qxdyIg5kzZ85hcdL2Y2ndLaTvyYCkUUgccB5P+7s4wPr162c+6urSPh9/kvj+F154IXeuuDjg+uLHYcXoOspEHCS5++67wyOPPGKvUZuHHHKIdTsgEOJf8vPPPzcBwc2ROBBCiIqTFAdffvllaNWqlfmaNWsW3n//ffPHGTBgQBg1apSNEnvwwQcjb9l88MEHuVbyyJEjbdQZ5wC6LNhO2l133WX7C1FRcfDOO+9YQTvHulGz9vLLL0dHBGuIxve7rbPOOta94hBkyV5TF5e8XhqwcXFw6qmn5vZxngsvvNDOkSYO6LpxX9zOP/982++kfReMv5k3rj/99NNcUX/c9tprL9ufJUURBw6pJ1Tssssum+tKGDJkiC3GxI1yYUCdQtbKSOJACLEg4eKAxhhQt8U2o8eSzzlasVdffbWlwxEOHLfIIovY85lp7oHCOGoYfvnlF9sGRpg1adIkbL311rbtQ89vu+022z7ooINsG6MLeZNNNgkLL7ywGYG1EBURB2Q9mH6f47h26hxodNLQxAik4OLgzDPPtGNo9XMP8D355JN2zK+//mqfhY9gzHWuuOKKto0Rf+LigCL6yy+/3AQAc/RQdP/dd9+lioMNN9zQtgngfP55551nAoZr8EYv35fvQlc7x2CsQ8T72rVrlyuCROjh429EzZ5/F5YgeOmll+yYrCiKOEChHX/88aaSjjjiCKs/cKjypCDRb/CSSy5ZlNSXxIEQYkHCxQEFiYMGDbLATxCh4ZXkzjvvzD1zDz30UKsd6Nq1q20ffPDBdgwtXbaZwM4hqOIrJA6oN2N74403tu5lOOOMM8znre00KiIOWHuHY2hEfvHFF5E3hA4dOpjfMyOIAwIvc+g4F1xwgR3j4uC5556zbebXYUQCIIqaN29u/qQ4uOiii+wYIOjju/TSS8sUB/GuCLp08CEwwM9xzz332Dawz8/l3QqIKoRI/LtwHznmgAMOiDzZUBRx0Ldv33D00UdbqoRuhSQTJ060/QxjIZ1TDCQOhBALEi4OKErEeI048EATxwPqRhttlOsLJzjiwwhs+MnyEmgdzwyce+65tl1IHCAiHDLG+LimQsWQcyMO6C6JwxT8+BEk4PVtcZLigFZ6nTp1wkMPPWTbjgf2uDhAHMXjFq1//AiLNHHQrVs3Ew40gsmM06WCUOMYBMDgwYNz74mPgqCh3LJlS/PHxQH3n3O47bHHHnYMxfxZUtRuhSSIAleXxcbFwb777ht5hBBi/sXFAUGP1mWPHj1smxEKPGvjuDhYbLHFbK4ZzAsXMW/14iNlP2nSJNsmULKfEWhQSBzE+9ddHGBVIQ6Swwp9SCVCByoiDpiVF+GUxMUBwd3FAYIoDqPt8CMOKEykHoFtFwcUFtLab9SokYmrtdde27oVOCYuDuiyQdjEwce+uDigS4NzJO2OO+6wY7IiM3HAUEV+rGVNakFB4pprrmmFiMXGxYGneYQQYn7GxYEXJJJ6J4jgo48+jouDQubiwAM7aXUEAV3ALK8/depU219IHHjXBMyP4oDrqIg4gGuvvda2EQevv/66iQK2WVzQuw3i8cbFAQsR+n100sQBMbIUZCYOmO+AL7nDDjtEnjmhcAZFRfVnsVG3ghBiQSIpDoDqfHwETO8KABcHG2ywgTXk3EiFP/PMM7mhevzLgnlkI0iNE6zuv/9+2welEAf8G4dJ9fC/8cYbtl2WOKDoEOivr1+/vo28iOPigMJLFwd85/iQew/unh2Ji4PevXvbaz+HQ3EkPsQB93S33Xaz7bjQ4fr5LPxxcUABqGdqgPoDihLpvsiSzMQBFZp8yXgxSxpUyPoMiVRodurUyaps/ceZFS4OkqpQCCHmR9LEAcXg+AmYFMX57IguDmiY0W8OtMCp/aJPm2nwHQI2x2LJ1nZViwOmIqamIGnUoiFcKGpfeuml7RrxP/vss9Ynz3fz4ZRliQPS/cCEQ3SpEAfin+OZFmoOmJOH78u2Fy4So9q0aWM+AjvbXieQFAfUJnBPr7rqKrsmfJ6pZqQB2/HPf/jhh3PvdXHAd2Obz0DcUVzqoxq41izJTBzQl88XILXFDUJlpRk3jT84rxlz6jenWPMcMHOYEELM76SJA+f000+3faSymRjp8ccfzz1rmXiO56+3wLF4pT31Cu4n7R2nqsVBIfOaB4I6I9qS+0866STbD2WJA4bJO/3795/jPG4+lN5HWmDbbrutZRx4TdcKQzwRX54FQBzwPXzY5Lrrrpt3TzEXB4gKBEd8X9xcHJAliA+xdKOroSrWcyiLTMQBw0QookDtoEQJxHvvvXee+R+YFJErMYypPxlmk/WoBYkDIcSChIuDtCJrGmg+fI4UNdX3TIDkLWM3xvxfdtlldrzDs5hWK33pBOc4Tz/9tD3Pfd4agjTnufLKK20bRowYYcew2F6h5zrBmEWHOI70OmIAI7WPLz7XAtkP3+8WT+GznVw/gi4T/ARzh9EYdJFwfhqm7CeTwvVTZAj+Pr8Ot3jXCkKLbgPPttBV4cedcMIJ9n6Me0h2wEEg+L6kuTgBMhbJ/fHRIFmRiThAiTJspaxiP4o1+CNQrYkC4jVdDFR68of2sadZIXEghFiQYCgihXavvvpq5MmH1igFeQQ8h1Q9PjfS22nwjH7rrbeircLw7OY8WXcLzysEcLIA3qUCrAPk4qC6TjNdTDIRB6RVfFVGQIWiRlE8Tpo4oEARRUTKhtm14kUYVY3EgRBC1Ex8EiS6QYhNmBc8YvGWe00lE3Gw4447WoEIxSIYRSbccEQD/ScY3Q74KHahH6tt27bhmGOOya0ehjHLV1ZIHAghRM2ELgCK5uOz82IU0FMXkTZZX00jE3FAMSEzOdFNwA1nLmr6WtyYMdGNcZ5kC9xISd133312XJYTJEkcCCFEzWbs2LF5sSnr7uz5iUzEgUNRCgE4vtoXRSCu0gpZ9+7do6OzQ+JACCGESKfKxQEpGYZvUNXKYksEYBb0YPujjz7KiQNWmaL4kJW03JgxUeJACCGEKC1VLg6oAmVYBzM7+XzSjDtle6uttsrLHLDdsWPHnHkdgsSBEEIIUTpK1q3Agh5J9tlnH4kDIYQQosSUTBwwrzXzWMeNmb0kDoQQQojSUnRxwBCRQw891PwY03n63NQsYMHc1MwfnTUSB0IIIUQ6RREHTCHJvNO+yBHZgxtvvNH2IQaYs5rX8WEkTMvpi2RkgcSBEEIIkU5RxAHG4koEfEAEME0lwZ+5rtPEwTbbbJM3y2JVI3EghBBCpFMUccBa4L4eNlkDVqNitkRfS9vFwe23324CgdEOLKcpcSCEEEIUn0zFAdMfMx0l81izfgJigVXAWrRoEUaOHBkdFUwMEKgZ7tigQQN7jbGAU1ZIHAghhBDpZCoO4jCdMiuGXXzxxbb8ZRyWrkRAJC2+UFNVI3EghBBCpFM0cVDdkDgQQggh0imZOBg1apQVJDJlcimQOBBCCCHSyVwcfPzxx2Hvvfc2QxA4H374oQXnww8/PPIUF4kDIYQQIp3MxcEXX3wR1l57bQvEzZs3N1EAEgdCCCFE9aQo3Qrjx4+3QIzdeeed5pM4EEIIIaonRREH//zzjwVjAjGZBHjrrbckDoQQQohqSGbiYMaMGaFXr15mN998c+SdTevWrSUOhBBCiGpIZuKAbEHPnj3DIossEmrVqhU6deoUpk+fHu0tvTiYMGGCxIEQQgiRQubdCpdccokFYSw+WqHU4sCXjpY4EEIIIfLJXByMGTMmrLrqqrbQ0nfffRd5Z4uDvn37Rp5ZTJs2zdZYGDp0aOTJBokDIYQQIp1MxEGXLl1sNILbwIEDw+DBg/N8rVq1suA8YsSIPH/79u3N37Bhw9xiTVnw9ddfSxwIIYQQKWQiDs466ywLvPNqLNyUFSpIFEIIIdLJRBz8+++/YebMmQXtlltuscB8/fXXp+534zxZcccdd0gcCCGEEClkXnOQhL7+li1bWmCmFoEuiLFjx4apU6dGRxQH1RwIIYQQ6RRdHAwYMMCCMkMbGep4yCGH2PZ2220X7r333uio7JE4EEIIIdIpqjjo3bt3qFu3blhllVXCuHHjzPfXX3+FU0891QJ1nTp1Qo8ePcyfNRIHQgghRDpFEQcE4rvvvjsstthiYemllw6jR4+O9szijz/+sAJBJkti0iRqErKsNwCJAyGEECKdzMXBl19+Gc477zwLxCeffHL44IMPoj1z0qFDBzsO+/777yNvNkgcCCGEEOlkJg7ee++9cMopp4RlllkmbLDBBuG6664Lf//9d7Q3nddeey0su+yyEgdCCCFECclMHBxxxBEmDPr06RO+/fbbyFs+r7/+us1vwMJNWSJxIIQQQqRT1ILE6oTEgRBCCJFOScQBXQZMjYxlXXhYCIkDIYQQIp2SiAO6GgjM2J9//hl5i4vEgRBCCJGOxIHEgRBCCJFHZuLg559/tmWaDzjggDB58uTIG8J///0Xzj33XAvM559/vgXpUiBxIIQQQqSTmThAEHh24MEHHzQfwsCDcrNmzeaYDAk4xi1LJA6EEEKUkmLEusqSabfClVdemRMHo0aNslUYX3rpJfOtv/76dsxdd90V+vbtGz766CObMGnttde2/Q899JDtzwqJAyGEyI6nnnrKnu1ZD0uvKj755BO7XqxQRvvrr7+2/e+8807kmZOffvopd55HHnkk8s4JEwIyYzCTA1ZHMhUHjEoYMWJEeOutt8JGG21k6ykcc8wxFpRXW221sOmmm9qUyS1atAh77LFH2HHHHW0ftvvuu0dnyQaJAyFEqfj000/t+VfIjj/++PDbb79FR1ccGls8OydNmhR5qp77778/9ZoJdkyF7/jzPMtrqQo+/PBDu/6VVlopF39OP/30vO8CP/zwQ9h4441tf5MmTcKRRx4Zfvnll2jvrCzAjTfeGFq1apU7T7169cI111yTNyrvlVdesc/bcMMNbZ2hhRZaKFxwwQXh888/j46oHhSlILF9+/bhtNNOC1999VVYa621whZbbBGeeeaZ3A18+eWX7bhHH33UtnfbbbcwePBg82WFxIEQolS8++67uedfITv00EOjoytOgwYN7L1XXHFF5KlayAJstdVW9hkENYJh06ZNc9fMJHbO/CIOaLlznVtvvXU4++yzc9+FGX6dKVOmhE022cTq6PjO2FJLLRX22Wef6IhgMwD7ew888EA7huDP9u233x4dFXIrEV944YXhm2++CVdffbVtc1+rE5mLg6uuuspWYmQ55l69etlNYCVG1BqvMRcHjRo1Cu3atSt3muWqQOJACFEqXByQNR05cqQF3bj5NPLdu3eP3lExshQHZIIJoJz/jDPOsOsERpzxGrHg3cWQtTigG4BGZnk8//zz1q1diDXXXDMsvPDCFpeIC3yX2rVrW0PW2XXXXe27xGf7PeiggywzwFIB8Oqrr9oxJ5xwQvjnn3/Md+aZZ5qPY4G4t8QSS4Q999wzF+fIEHEM9+++++4zX3UgU3EwderU0Lx587Dyyitb+qVly5ahS5cuti9NHBx33HGm0IqBxIEQolS4ODj66KMjTz4sXc9+WrVz01iKi4Np06ZZV27aM5UUOPuSxiizQjz77LN2bmzMmDGRdzZ8JkHUSYoD4gGNv+222y7PunXrlhvS3qZNmzB8+HB7HYcW+n777Wevp0+fHs4666yw6qqrWqD187A2j/P222/n/EsuuaS14Pn8NHbeeWerj4uDWHBx8MILL9g5qA+Ij7x77rnn7PshAIBuBrbff/992wa6JhixRzac66b7gGPimXGExEknnWT+fv36Rd7SU7SCxBtuuMGEAoWHkCYOionEgRCiVJQnDh5//PHc85EiOIf+63POOSfP4kVvcXHA+ja8phv3jjvuiI6YRf/+/XPnjxvBeebMmdFR+dAtvO6669pxaeIgSVIcXHbZZbbNsvyIH1rY/rkeUGmxsyYPrXBn2LBhoX79+hZAgXoM3kMWg/PwXdlebrnlwptvvmnHbLnllrlzk/7nuGQNQSFY24daOBcHAwYMsPNcfvnltu1URBwAWRb8HJ8mDoCFCfGTUaguZCIOJk6caN0I/EH5A/JjI1Xz66+/RkeEsP3229vNoCiDVRuLjcSBEKJUuDjYYYcdwsCBA+ewFVZYwYLonXfeacVspLwJiqSeeV/cOI6WMrg44NlLoKG1TZCrU6eOCQ645ZZbrKuX4/h8jqFg3M9XVmONQE+/e8OGDa0lTSbAr9nT604hcUBrHsiIHHzwwebbZpttzHfTTTfZNl3QQEDnM/A9+eSTJkrofuZ7erAnC9KzZ087pnfv3uZzcbDvvvuWmQ1JwrVxP3mvd1lURBxQdO/3dF7EARmL6kIm4oAhLHxRzFNBSVq3bm37Ge6x6KKLWjFiMZE4EEKUivIKEpdffvlcgARqD/ATgC666KLw9NNPWyDk2Ynf+7RdHHTo0CGXAaAKnoDqBW9rrLGGHcMIMW+wTZgwIWy++ebmJ2CXBUPOERMIEI53ozCxrIJEsseIAETE77//Hr777jtLuXMM5wMCMd+ROgDS8GQr2L/ZZpuFH3/8MScw+J68382zB4wUQEy5OCjvuyR54IEHbCQC7yV20TVTEXFAlwavMYmDMvjss89yP8Avvvgi8s6GHwd/APpheL3iiiuGtm3b5gpcioHEgRCiVMTFAcO7u3btakZ9Fj4PqI4HUTKxcWhN42d+GIh3K8Sh8p4WMXUD/mxOjq9nUjr8FQ2opN/9un2IHyLEU/tpBYl+HfTzs8/NxQF4YEdAuDjwbhEXB4WMYZzzIg4cMg68n6BdEXFA1w/FmGxLHJSD39ykOCAF1KlTJ9t38803m8+LMUiDMYFEMZA4EEKUChcHtPjjffzup+EUD6qFxAHQ1VCeOPBiQgr5KisOKMajMPDSSy+NPLMhdc+zlPd7xiMuDviOCANqCjAKF5lIiGJEjomLA2+Fn3jiibnv7fcinjkg25E0WvowN+KA+gbeG+fuu++29xO06WahC6UyNQdcDxkI/BURB/HRHqUmc3HAj9GhKtNvAj9mn/SBf72fB4FQjAyCxIEQolS4CEgWJMaDSXwiuHkVB15kR5dEIXFA3QL+QgHVBQZBPm2pfQ+oaeKACYR4jVFE6SAq8MXFAXUFxAOm2CcTwXBBbzRSkMn3XXzxxa3bwWG0Q+fOnXN1AhUVB7yPCfmow4gTFwfAd+Eexyc98qLRpDjo2LGjbQPDLfFxPd4twt8hPqqDBrOLnhoxWsHFAQUvDuknfARkJn+IQ52CCwS6GJgYgu6JrJA4EEKUikLiAIYOHWr9+QR6r9ovJA4I2ASb8sQBXbcUEQIT0nEMoxgIWA7b+AsF1Hh3cdpoBbIg7CtPHDz88MO2nzkDEAX44uIACPR+fLLF7jMZUr/AME2EisebZEFieeLg2muvteMQHNxLh/fhd3HgBY/33HOPbQPXQaEnXTvgI0Di34V7gc9rQqBx48ZhscUWy/1tuR8cQ80Gv4vqQmbiAHXIF2a4ClOFoliZ2INq0PgPMg59Oww74X2kcY499thoT9Xj4oDil+o08YQQYsGnLHEAzKjHfoYj0rodO3asbdOKZlge0Ce/1157mZ/gCC4OaL0ywoEJlpj1j75sZvgDhpMz7I/jCLCkzRETnJtJmejnLwSz+vE+AiMt7rjhZ+4BHx0QFwcEca+nYM4BPpPrYRtLigPeQ7ElATM5T8OQIUNyk0RxHcyfw2vugbfsjzrqKPOVJw64Vp/gCPEU/y507fh3YQQeQ/EJ6n4M95RaC4cMQJ8+fWwoph/j95QiTocifM5PjOMY/mZ8Tx9xUl3ITBzwgybo0q9E5SkpMhRxeTBmlwwCQ2OyxMUBxvAZIYQoFuWJA1rVHjwvvvhiC/SHH364ZQlo5fKa4MV+5ibwtDuT9fhzjWyDT21MIyg+Ioz5/QlufixGoKUhVxZcB891juU5nbT4CAuCLj6vF0CoUIjux5Id5lwUZDJSIg7DHAnECIo0uH7eG7e4iEAk4IvPl1AIro8Mt18XRnrfr9th7Qi6ydnP8ErOP378+GjvbG699dbcOTiGroU4/G39ms877zwTJdUpY+BkJg6qOxIHQohSQbcqfff3339/5JkTWqs8n+Kz91Gk588tjEwszzKHIMN5k5Y2OyABNn5MvHVbarxboZB4EtlTFHHAiAVSJkkF5aBW+Y9QTCQOhBDVGVrPdAHQWncoWMTnFp/Od0GADAitcroNSLtXt1R7TaIo4oBVGQnCydQRMLMUE35Q8FFMJA6EEKJ64aMEMIrURenITBwwHIf+MbIGDBNxcUCRIX5XhPS7sE/iQAghajYU9VEcyZBEXovSkZk4GDFihAVexABzYPOaqkzGrTIigeIUYN5vimVQjMVE4kAIIYRIJzNxQF8YgZcqUBcHGENLWF/boaqT4RzFxsekssAJK0QKIYQQYhaZiINLLrkktyAIY3J9BUaMLAFDVEgdMRsivvjkEwxhZP8TTzwRebKBjAafrUmQhBBCiHwyEQfMjf3CCy+Y0TJ3YcDKYkw5iZ/JIvDR1bD//vtbjQJZBipU8bOUc3IBi6pE4kAIIYRIJ7NuBXjppZfyJuXAfL5wJvZg2yc7QjAwmxQ+ZtZi9q8skTgQQggh0slMHAwfPjzXtYAdd9xxtgY5rxnH6lNeMpOig5Ag00CNQtZIHAghhBDpZCIOCPhMnUntwG233RY23XRTW+yDearpQnDBgPk6C7/99ltYYoklbCWuYiBxIIQQQqSTiThgik9WFWP9aroLCMKIA/AhhMynzdzhzBEOLA6Cn4WaioHEgRBCCJFOlYuDzz//3FbHGjx4sG0zh0BcHIwaNcoWYJo5c6bN550UB8OGDbPtrJE4EEIIIdKpcnHA2tssI8qKYBgrTmHrrruubbNcJ4uDsPAIa5Czzjj+1Vdf3YY8su531rAuuS8fygpaQgghhJhNJt0KDFk8+eSTLfgyPBFuuOEG295ll11sG8gc4HPztbOzhvUc/DO1sIcQQgiRTybiAHxpUeY8+Pfff0OnTp3C4osvHoYMGRIdESxLUKdOHTuObgWOKwYSB0IIIURhMhMHjEog8B944IHh0EMPtUDMqIW4ALj33nvDQgstZPs23njj8Ouvv0Z7skXiQAghhChMZuLA8dEKbnfeeaf5WXth2223tVoDFw8bbLBBuOeee2x/lkgcCCGEEIXJTBywVPOll15qkx2tscYaNhVyixYtrACRqZHxNW/ePIwbN87mRTj//PND7dq1LdvA/muuuSY6U9UjcSCEEEIUpsrFAUMYmavARwOQGUAAQKtWrXJB+dxzz80t2+x4geIee+yR6SyJEgdCCCFEYapcHDDJ0emnn26B/p9//snVGLBM81FHHWXrLeD/77//zB+H97KPf7NE4kAIUQp4Ht599925eWDmJ7777ruw2WabhS5dukSeOenbt69lgNu3bx95QjjnnHPMd9FFF0UeMT+Qec1BdUTiQAhRChjmzXOHqeVZoXZ+gqX1ufazzjor8szJlltuacccfPDBkSeERo0ame/CCy+MPGJ+QOJA4kAIUSSOOOKI3LOH1WezzpJWJRIHNQuJA4kDIUQReP3118PCCy9sRdq+lH1Zc7u888470auqZ8SIEeG9994LzzzzTBgwYECqSPn4449tn9sFF1xg1yxxUDOQOJA4EEIUAdac4ZlD3ztzvPC6Z8+e0d5ZMBncTjvtZNakSZPc64EDB9r+F198MefD+vXrZ/Vbf/31V+jRo0fePrfrr7/earkczsHS+KyA26BBA7sOshivvPJKdESwYnEvKm/cuHFOzGASBzWDGikOKKxh0iV+sBIHQoisefXVV8PSSy8d6tata9vff/+9rUrLwm9ff/21+aBNmza5ILzPPvvkXi+yyCLWcuccTDC355575vaRfRg9enRue6mllrI1bg477LCcD4EAfh34mJSO47BatWrZWjcOYoFj1lxzTVuLhvexRg4+iYOaQY0UB+CrMkocCCGyhnlbeN64OIDjjz/efL179448s8UBa9BMnz49/Pjjj5bSx4cxHf2MGTNsnw8NT4qDQYMG2bmYP4ZAjq9t27bm8+uge+O3334zHzCaALv99tvt/cw3gzBggTzHBYnEQc1A4kDiQAiRIfTnd+3a1Z43PHcI+JgXJ8Zb7C4OyBo4XgiIjRkzJvKGcMcdd5iPRe1cHGyzzTbhp59+io4IYeLEieZPigMyBaye64YP69WrV+jTp4+9vuKKK+w9jgoSaxYSBxIHQogM+eWXX+xZU8gInhQIwtyIA5a+x/foo4/mxMEhhxwS7Z1FIXFQyBAHXocgcVCzkTiQOBBCZAgzxvKsoaiPvvy4rbXWWraPVWwpGvRZYudGHMS7FSoqDuhW+Oqrr3LGSIr+/fvb4nc333yzHVMZcfDyyy/bMXFxwHo6+CQO5i8kDiQOhBAZcsABB9iz5r777os8s4mvTDtt2rTw5Zdf2uu4OBg+fLgFc/xxcdCxY0fzIQ4+/fRTqxNg7Zr4tPQEfo5JEwfUJDjUPbDeDaMeHnroITtm3XXXzVspt127duYvSxy4SImLgyeeeMJ8EgfzFxIHEgdCiIwYP368jUhgdBR1BmlsscUW9iwqJA7ABUZcHDDsEd+wYcNsu3PnzrbNujXw+eef5zITLg4YxshoBnx0AVx33XVm1CDgo1vhgw8+sEXx2L7kkktsET2Gf/twRomDmoHEgcSBECIjGC5YXkAlpc+8A2eccUZOHJx55pnR3lmkiQPvVmAoIrg4IIOAKGAeA7b5l1VxnaFDh+bqANzYZojklClT7BjO3bRpU9uHUGClXAonGdFAt0MhuH5Ex8UXXxx5Zg2fxEeho5h/kDiQOBBCZMTDDz9sCy2V95xBGDBb4e+//27HM1wxzlNPPWWBOSkO8NGtwNwtBG+eaWQUOIdbXBg4BOz4MWwnYQbF+Dn4jPvvvz/aKxZ0JA4kDoQQ8zmezseoURBiXpE4kDgQQsznSByIqkbiQOJACDGf4+KAwscJEyZEXiEqj8SBxIEQYj6HWRgZhhhfYEmIeUHiQOJACCGEyEPiQOJACCGEyEPiQOJACCGEyEPiQOJACCGEyEPiQOJACCFEjG7duoWvv/462qqZSBxIHAghhIjBwlTrrLNOGDJkSOoMkzUBiQOJAyGEEDF8FUysSZMmthAW1rVr1zBz5szoqAUbiQOJAyGEyBRWnLzyyitLbuPGjYuuqGzi4iBpRxxxhJ2rf//+0dELJjVeHGy22WbhhRdeqFKr6X1VpYAZ4j777LNoK4Tvv/8+9W/jxupx8xMssuPX/vPPP0feED766KO871UKu/baa0OLFi3CaaedFv78888wcuTI1ONKZSyJzPUlrW/fvqnHV4UNGjQo9TPnxlgJMe3c82qskJj2eVnaSiutNEeQLYUtv/zyqdeXtLT3Jq1+/fp27BVXXBH9b1ywqPHiIAtbf/31Q/v27avUmBL1jz/+MOMh7P6xY8fm/BdccEHee2qS8fBZbbXVctu+VG4hoz8x/v7qbssss0zu2tu0aZPzs9Rv/HuV2vbee29b4jdtn2zurG7duqn+YhoBcNFFFy2pHXbYYeHBBx+sEtt8881TPyNuZWUN4rbRRhvZORfUmoQaKw5ICRFkszB+NGk/Jpms2Lbccsvl/TYRrvjbtWuX568K48Gb/Py5MYRF2nmzMlqR8c+nRZ12XKnsjTfeSPUX01hCuqbBMtu1atXK+224dezYMXdvpkyZEr1jwaTGioMs+eGHH8KoUaOq1HbZZRd7+JbKEFOkz3yboT6PPfaYvSZjkXbN1dni3wXr0KGDtQDiPmzw4MF2/DbbbJPznXTSSXOcr7raF198Ef0qZzFx4kTz0wdc1UyaNGmOz58bK3Yg4t7EP/+nn36K9oiaTjx70Lp1a/t/36NHjxq1doXEgRBCCBGjTp06lj046KCDbEGrmojEgRBCCCHykDgQQgghRB4SB0IIIYTIQ+JACCGEEHlIHAghhBAiD4kDIYQQQuQhcSCEEEKIPCQOhBBCCJGHxIEQQggh8pA4EEIIIUQeEgdCCCGEyEPiQAghhBB5SBwIIYQQIg+JA7HAwSpqNXUltQWNf//9N8yYMSPaSmfmzJl2zH///Rd5Fgz8e/3vf/+LPEIUD4kDUWFGjBgRbrrpJlsHv6qYMGFCuPXWW6OtORk7dmy49957o63y+eGHH8IWW2xh66/zekFk4MCB9ndIBs0///zT/NiYMWMib/kMHjzY3vPEE09EnuwYPXq0fdaHH34YecrmlVdesbX1X3rppcgzJzvssIOtu//QQw9FnsrTt29fu7633nor8lSet99+2851++23R57yGTRoUHjnnXfs9R577GHf6+uvv7btOB9//LGde+TIkZFHiKpF4kBUmG7dutnDiuA0t2y99dZhvfXWm8NatGhh66ZfddVV0ZGz4aG46qqrhpYtW0ae8kHAcI1YVTzgoUePHnatPOznhXfffdfOUZbttNNOYZNNNonekc72229v32/y5MmRZxY///xz7rvfd999kbd8dt99d3vPLrvsEnnKh+/y0UcfRVtzMnHiRPs+yWu888477bOuv/76yFM2bdq0seNPOeWUyDMnRx99tB2zzz77RJ7yWX/99UP//v3nEJDLLrusneviiy+OPJXn0ksvtXM1bNgw8pQP3/fEE08Mf//9d544GDdunN1PF4S33HKL7WvatKllV4SoaiQORIWZF3Gw9NJLhyWXXNJaZnFr1KiRnbNTp07RkbMgo9CqVSvbVyxxcMcdd4SOHTuGb7/9NvLM4rTTTrPzvfjii5FnFk8++aQd/95770WeWV0a+NKsdu3auWsry+rVqxedLZ1SiwNa6HyXxRdfPDz99NORN5+ePXvaObnWBx98MPLOvThYffXVLXPw+uuvR545IZPFOV0c+N8FAVMIfnurrLKKZZjIuDhzKw4Qtc8//3y0lY+Lg1NPPTXylI+LoUmTJuWJgwMOOMBee0bIxcFhhx2mbgeRCRIHosJUhTggAMetkDjwhx+Zg08//TTyls+8iAMetLwv2SIuJA66d+9u/sceeyzyBOv3Jlgce+yxZuxfaqmlctsYWQj8Tz31lB0fN4RQWeKAQMt7r7zySjs+Dt0D7Ntmm23m2EdQ/vHHH6OtfOLiIC4w0sy/iwsdriMNPv+YY47Jvc+7EeZGHJA6X2655Uwc8Fu58MILc+c7//zzc7+hNddcM+eP2yOPPBKdKR2EAccdcsghkWfuxQFdWBy/6aabhu+++y7yzsqc4KdlX5ZISRIXOi4OOnToYP9iiANqEXi9zDLLlNndIsS8IHEgUunSpYv19zukOUl38lC68cYbzcd++jx50POAnTp1qvnTQBzwXgILD/TNNtvMgnezZs3M7+KAjAH7ePBdfvnl4fPPPzd/kt9//z188skn0dZsyhIHpJC5Xt6bRlWIgyTsX2eddaKtWZx77rnmp9VNwN51113DCy+8YPtWW221VHFAoOW+IJZ47+mnn261GPhoBcP+++9v+2jR448b/r322suOSxIXB9wfXvfq1cvun9vee+9t/gceeMDeQ4obfzwgJiEoIgh5X2XEgWcfVl55Zfus3Xbbze4lv0O2uQd0STVp0sS26f7heOzxxx8PU6ZMic6UjouppDhAjNx8882Rp2zIUvhnDh8+3H5j//zzj9UN4Nt5552jI2fDdXGfsbiI++WXX+xaeB91FIg8P/cRRxxh/8bFwcYbbxy9cxYIEs45bdq0yCNE5ZE4EKkQoOgrJTBi8VbgIossYj72uw/zIJWGiwOyD3FoKeN3cUA6mG2EQVkMHTo0dx1xO+igg3LXw+v4Ph6m+HnQplEKceDnePTRR21fIXHgAX6jjTYKN9xwg5n/Tbp27WrHIA5IS/t+N2/dxq+D4Of3heDLfsSBC4xtt902OnIWxx13nPnffPPNyFMxnnnmGbuGn376ybYrKg6mT58ettpqK6tJKStztNhii9kxgCDg3ATkQgKQFL1/b8QL18ZvyUEcLL/88tFW+RDouVd87oABA+w3xnf1Vv+KK66Y+zw37xbCXGwBYtv/ZnwvP2aNNdaw7gteIw7uueceex0XBwiDDTbYwPz8HxJiXpE4EKkQoBo0aGCB748//jAjlcvDh9S2+0hDe9AtTxzUr1/fUqRkBWhREhAPPfRQe6+LA1pFnNeLrM444wwLXsksAQ903rfWWmuF9u3b55m3rilU41xHHnmk+TkWPy3NNOYHcRDPzlDZjg9x8Oyzz9r74v37jgf2+HVcdtllufvF/WA/4oDz47vkkkuiI2cxN+Lg1VdfDR988EG0lU9FxcGwYcPsuLPOOivyBLtffD+yBECtBwLRxcF5551ngrVfv37hggsuCIsuuqj9ZuPwu7rtttsKXsPcigOgzoTf2f3332+FjvxWCdTUzMSFQOfOne3++jZ2+OGHp2bHvLsN4+/28MMP22dQX+BZBDI+CAGyDPzt8SFGyKgIMa9IHIhUeNgkCwEL1RzQzYC/LHFAwPCiMvphEQuAuCAdS7CnSyEOLTAe/qR5k8PBXBycc845kWc2nn3wIOJwLP6sxcGvv/5qfcfef0zAJxjzEOcz5kUcECAcFweIJ/rP6QpII00cxKlIQeLciAOyD82bN88r1HQqKg48g8H35r5hiEqEACNf+Btvt912tk0ABkZ5sB23tFEwQC0D4sHvu1MZcQD8hgnovXv3Dn369LHajC+//NIyJ3wPRAu/B+8SqFu3rv1/StaG0H1Hd0qdOnXsOIyAz/up7+Cecu1083h25K677sod68MghZhXJA5EKmWJA1r7Dq0mht/hTxMHVNQTDDGvYUAccH4CPA9QWoe8f4UVVrC+bCBN6hkJ6h+SZCkOyDj4NWN+HbSo436CFP6kOCBdTVDyVDC255572jatVt6Lr6rEAUZAKkR54sADtosD5hbwbgBnbsSBF01ST/L+++9H3llUVBzw3fwebrjhhvaeePEjffvcR4JtnN9++838BMyy8ICavI7KigPEDKMfgHOcfPLJ9trFgWdAXBxcccUVtp3E6ywovqQ7gdfx0QrUp/Cvnx/8u9CVkbwfQlQWiQORCgFqiSWWsEDr5g9pApX7jjrqKPNhaeKAh/u+++5r1dwEH97Trl078xFsabUutNBCto2RHgfvV6XFjQBJkoU4oOXt1xE3WqC8jz7wuN+r5MvrVsDoR3bmRRwwjJDAifl5CCI+rJGJcWhhk2J3yhMHjJpgP61V3ktqPFloODfioKwhlYXEAfei0KRVnkaPT5w0atQo8zHyw3+LGL8p/HyX+KROdCf4fcO4j/x2KSh0mKCJYs40ccBEXdwbgjSFg3EYVUGGi5oHzsHwS2/Buzjgb8pcBWQG+C1QtJiE3xEZAgpN6T6ID2Xk3vjQXgyR4NfBUEl8hTJHQlQGiQORCg+zinQr8NA9/vjjzV9WtwLvad26tbWcEQCIAoyglwyGFHbR+qLeoNAELy4OaEF9//33eeZ1DEOGDMnzcyz+NHFAi4tsRRqFuhU+++wzCxgEvELwPqyqxAH7yLBgpK7xeUEiMASUYYakrenegDRxQCEd9wRh4P3bBDhqDdIKAP0c8cr+QhAAqSHhGpNp+zRxQGufbqYdd9wxlyqnb57rY6gemSbew++L3wzvdXHAkL/435haB/wI2fjfk7+v3zc3uiX8d0iNg9eqUBuD0GB0BxkfXvN/AT9dEYwIcAjcdOtQlIhAIyOA6HA4N+fEkmI1CaLFZwtFhPnfhc8Auiy4f1546XUdiGu63srKHgkxt0gciFQqKg6gIjUHvIdjeIgyhtyNAOfBkJoDghPHJQvJkrg4qKjR+txyyy3tdZo4IAjxgOW8SQqJAyB1zvUXmgjHP788cUDRJJQnDuIFhwQTfHFxAJwDv88qmCYO6MPHF7eK1BzQep0XXBzQ8uVvjXn3DObzC9Cy5zX3xfdxDfgIji4OMP62ZHV8G0sbQpiE36v/Dp977rncexEDcO211+al/2nZIzgdJjniHvOeQqKJ2gs/L0MTy4JuE78nPqQRQxwwZwN+BIh3TbANiIO1117bXgtRVUgciFQIUARRagKAWeS8T/6iiy6ydKmbz39QEXGAwIiDAPFgyDAtHuo8dL3vlNYgNQ08ZF977TXzgYsDPvubb77JM3+wklZ2H9dPYEIAtG3bNjrLbBAHvCdtNrvyxAH70uoi4Oqrr7b9jM7gOxAIuQ4EAmlhqtXZz3h9hm/yfZMzNIKLg7Sag6Q4oMuD85FFAA/sZAkcFwdkZ/x1ZcUBczXEfw9xO/DAA+17u3m2AyNTwN+bYlP/O3m2w+HvRjcUx6d1K2DMEcG95P0+w2BFxEEcLx7FCLp0AZTHuuuum3sPn52Ec5IBo1iUGgIyM8lMShyKDLluahc4J9kftslgkLXAx/8RutkYecP/Hf8/yX0WoiqROBCpELBpkXhlOKl6Hm48iEit0jfq5g8uFwekhpOFUS4OeKjRb4vxYKOuIa2l7HBO3ofFCyERBwTAZGAErpfj09K4BJq07oN5EQeMSaff2eG7E6zIqFDMyH3kPjGmPZ6ZQGT5d8MKCQyYG3FAMWE8u+OBPV4v8PLLL1trlGv11HdlxQH1Cd5yR3zFfxtnnnmmfY6bC0kyAmn97mmUVXOAkY3y3xT1AvxOy/ouSQi2DDPkXPweMf+dMgqhEF999ZXVF/C+5MRD1Az40F++N8W4iG2EAnM4lIW/z4W0dyMgEuiCAf5f+CyViAgm/xKiKpE4EKkQsCvbrUDxoc+i6Lg4YEIebwlSIEgdQCFxwIOZYMOxpGTjgZEWlKegk5QlDgoxL+KA1nAcigI5HqN1SXo6CS1TCgm5Hz5sLykOaHk7cyMOkqSJgzh0ebB/XroVaPGfffbZZWaPIK3moDyS4oD7QoEen+dD/vh9IFIRauwnIFcUFmDycxDkCcCcm+JEfpuMICg0+6dPMJUUBwhQ/CuttFJuaKyPPuA9haayBhcH/ltkKCMCIF48CT7pEaNrhKhqJA5EKqR8k/2ohcQB1em0jGgt81Ck1VVIHHAO7xJAHBCUefAlJ4LhQUgqnqIsugfKmwo3TqnFAX3TBBosLUvhLU6+N8PQfMKfuDigNU4gpjgTXBxQN8H3wwg8+MoSB2Q0aMFzXCFxQFcG+4tZc8B9LlRsmsTFAfeK780IGAcxwN+A3wcpfAoNHQQL9zmecUpC6p/7iAhgEqM4TK/MOflsuqLSAnqaOKAugK4d/PHVJBEtjRs3Nj/ZDoaMJuc5ADI//H/i/6AvPMX39C4+shK8F/HOuch03H333XPMEyLEvCBxICqMiwNmaysEFdUckxQHnrqmniAuDkhvk3Yng+Cry1HcxygA0qZlpXULkZU4oGgtCYGJIE8BXUXwoM939sxHUhwQMBiWhs8r0F0cxAsfOR4fw/ni4gk/rUm6DDyoU1eQnLuAtD7H0MfOMWnigADOMT5VM581L7g4wOJZkLJwcUA3EtfB7wRjyB+B06faJpDTreDdFXxf3odIc3gf34eZOjkvw1HpEkkKXoffqqfvCehJ4uKAvxvnZoQDvv3222+OjAK/Mz8fRs0J3UtxuH5+uz5Kg+wIvxe6Pjg/U1/jRxxwDzx7wiRQfCe6coSYVyQORIVxcUDNAcVuacZ+LC4O3njjDXsPDzuIiwPwoiqCr5+DVHtaS70izIs4IAAkv5NPgUvwSe7zhYWSXQJpUHjnIwnioxdcHFB4yTlJubONJcVBPKCSZiflTFAge+MwAsL7wjGG7LnwiuOjJtziLXIH8YZQ82MqMs9BWcyLOCDV73jXDQHSJ9fyVj4jIbiPnnZ3cUAWxQUVooAMF6KUgFsW11xzjb0HEZgkLg78u1FQGJ9nIgn31K+V6/CMAENjuW6KENnH746aFYQf9Q/43Bh54oWr/P+Kj25QN4OoCiQORIUhRU4A84CYNNKzPMwYe+6tVKq4SaXywGIKZTIITCpE68kFBPPg834elLyfueErGjiSMAbdF3maG3HAtLR8dkWNlC/jzD1NXJY4oHVIoOJ9rCzI++LFeDzc/Z7y0I9/jrdoKeBje8aMGbbtkBZP67qgm4bjEVk+QVISuhNI1dPtQDq+0CREiDmCGSIhXnhZGTyAMmNgRbsVyLAgDCjkGz9+vM1hwLXw/VwYAK1ov29x43cHvjASwsxHR1SESZMm2e+WYsIkBHT+nhRaEswZ+ujBviyomeF98Wug28GvmW4D/m78bRFk/I2YNhkRwPuSI1r4XSD2TjrppIKLTgkxN0gciLmGhxiTGSUtbfIc+n3Zx5A08GV8fW0F4MFGwKA1OK/QL0yamL75soq+qgoeyGRFyhIiFA5yD5gcqBBMDMUx1G0UG+ZbKG9Oflq7ZFfmFX4jfM/KigyCJu8vq2trQQMhwHee16yNEHODxIEoOrQY461G+mrZTivOqgzeJ10M/NqFEGJBQuJACCGEEHlIHAghhBAiD4kDIYQQQuQhcSCEEEKIPCQOhBBCCJGHxIEQQggh8pA4EEIIIUQeEgdCCCGEyEPiQAghhBB5SBwIIYQQIg+JAyGEEELkIXEghBBCiBgh/D/DklpM2T+WJgAAAABJRU5ErkJggg==" alt="1.PNG" />

 

首先我们需要知道这个未知电影存在多少个打斗镜头和接吻镜头，上图中问号位置是该未知电影出现的镜头数图形化展示，具体数字参见下表。

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" alt="2.PNG" />

 

即使不知道未知电影属于哪种类型，我们也可以通过某种方法计算出来。首先计算未知电影与样本集中其他电影的距离，如图所示。

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" alt="3.PNG" />

 

现在我们得到了样本集中所有电影与未知电影的距离，按照距离递增排序，可以找到K个距 离最近的电影。假定k=3，则三个最靠近的电影依次是California Man、He's Not Really into Dudes、Beautiful Woman。K-近邻算法按照距离最近的三部电影的类型，决定未知电影的类型，而这三部电影全是爱情片，因此我们判定未知电影是爱情片。

欧几里得距离(Euclidean Distance)

欧氏距离是最常见的距离度量，衡量的是多维空间中各个点之间的绝对距离。公式如下：

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2、在scikit-learn库中使用k-近邻算法

• 分类问题：from sklearn.neighbors import KNeighborsClassifier

Type Markdown and LaTeX: α2α2

0）一个最简单的例子

身高、体重、鞋子尺码数据对应性别

import numpy as np
import pandas  as pd
from pandas import DataFrame,Series

feature = np.array([[170,75,41],[166,65,38],[177,80,43],[179,80,43],[170,60,40],[160,55,38]])
target = np.array(['男','女','男','男','女','女'])

from sklearn.neighbors import KNeighborsClassifier
knn = KNeighborsClassifier(n_neighbors=3)

knn.fit(feature,target)
knn.score(feature,target)  #1.0

knn.predict(np.array([[176,71,38]]))
# array(['男'], dtype='<U1')

查看电影属于那个类别

df = pd.read_excel('../../my_films.xlsx')
df

　　

feature = df[['Action lens','Love lens']]
target = df['target']

knn = KNeighborsClassifier(n_neighbors=4)
knn.fit(feature,target)
knn.score(feature,target)  #1.0

　　

knn.predict(np.array([[60,42]]))

#  array(['Action'], dtype=object)

　

1）用于分类

数据蓝蝴蝶以及k值的算法

import sklearn.datasets as datasets
iris = datasets.load_iris()
iris

{'data': array([[5.1, 3.5, 1.4, 0.2],
        [4.9, . , 1.4, 0.2],
        [4.7, 3.2, 1.3, 0.2],
        [4.6, 3.1, 1.5, 0.2],
        [. , 3.6, 1.4, 0.2],
        [5.4, 3.9, 1.7, 0.4],
        [4.6, 3.4, 1.4, 0.3],
        [. , 3.4, 1.5, 0.2],
        [4.4, 2.9, 1.4, 0.2],
        [4.9, 3.1, 1.5, 0.1],
        [5.4, 3.7, 1.5, 0.2],
        [4.8, 3.4, 1.6, 0.2],
        [4.8, . , 1.4, 0.1],
        [4.3, . , 1.1, 0.1],
        [5.8, . , 1.2, 0.2],
        [5.7, 4.4, 1.5, 0.4],
        [5.4, 3.9, 1.3, 0.4],
        [5.1, 3.5, 1.4, 0.3],
        [5.7, 3.8, 1.7, 0.3],
        [5.1, 3.8, 1.5, 0.3],
        [5.4, 3.4, 1.7, 0.2],
        [5.1, 3.7, 1.5, 0.4],
        [4.6, 3.6, . , 0.2],
        [5.1, 3.3, 1.7, 0.5],
        [4.8, 3.4, 1.9, 0.2],
        [. , . , 1.6, 0.2],
        [. , 3.4, 1.6, 0.4],
        [5.2, 3.5, 1.5, 0.2],
        [5.2, 3.4, 1.4, 0.2],
        [4.7, 3.2, 1.6, 0.2],
        [4.8, 3.1, 1.6, 0.2],
        [5.4, 3.4, 1.5, 0.4],
        [5.2, 4.1, 1.5, 0.1],
        [5.5, 4.2, 1.4, 0.2],
        [4.9, 3.1, 1.5, 0.1],
        [. , 3.2, 1.2, 0.2],
        [5.5, 3.5, 1.3, 0.2],
        [4.9, 3.1, 1.5, 0.1],
        [4.4, . , 1.3, 0.2],
        [5.1, 3.4, 1.5, 0.2],
        [. , 3.5, 1.3, 0.3],
        [4.5, 2.3, 1.3, 0.3],
        [4.4, 3.2, 1.3, 0.2],
        [. , 3.5, 1.6, 0.6],
        [5.1, 3.8, 1.9, 0.4],
        [4.8, . , 1.4, 0.3],
        [5.1, 3.8, 1.6, 0.2],
        [4.6, 3.2, 1.4, 0.2],
        [5.3, 3.7, 1.5, 0.2],
        [. , 3.3, 1.4, 0.2],
        [. , 3.2, 4.7, 1.4],
        [6.4, 3.2, 4.5, 1.5],
        [6.9, 3.1, 4.9, 1.5],
        [5.5, 2.3, . , 1.3],
        [6.5, 2.8, 4.6, 1.5],
        [5.7, 2.8, 4.5, 1.3],
        [6.3, 3.3, 4.7, 1.6],
        [4.9, 2.4, 3.3, . ],
        [6.6, 2.9, 4.6, 1.3],
        [5.2, 2.7, 3.9, 1.4],
        [. , . , 3.5, . ],
        [5.9, . , 4.2, 1.5],
        [. , 2.2, . , . ],
        [6.1, 2.9, 4.7, 1.4],
        [5.6, 2.9, 3.6, 1.3],
        [6.7, 3.1, 4.4, 1.4],
        [5.6, . , 4.5, 1.5],
        [5.8, 2.7, 4.1, . ],
        [6.2, 2.2, 4.5, 1.5],
        [5.6, 2.5, 3.9, 1.1],
        [5.9, 3.2, 4.8, 1.8],
        [6.1, 2.8, . , 1.3],
        [6.3, 2.5, 4.9, 1.5],
        [6.1, 2.8, 4.7, 1.2],
        [6.4, 2.9, 4.3, 1.3],
        [6.6, . , 4.4, 1.4],
        [6.8, 2.8, 4.8, 1.4],
        [6.7, . , . , 1.7],
        [. , 2.9, 4.5, 1.5],
        [5.7, 2.6, 3.5, . ],
        [5.5, 2.4, 3.8, 1.1],
        [5.5, 2.4, 3.7, . ],
        [5.8, 2.7, 3.9, 1.2],
        [. , 2.7, 5.1, 1.6],
        [5.4, . , 4.5, 1.5],
        [. , 3.4, 4.5, 1.6],
        [6.7, 3.1, 4.7, 1.5],
        [6.3, 2.3, 4.4, 1.3],
        [5.6, . , 4.1, 1.3],
        [5.5, 2.5, . , 1.3],
        [5.5, 2.6, 4.4, 1.2],
        [6.1, . , 4.6, 1.4],
        [5.8, 2.6, . , 1.2],
        [. , 2.3, 3.3, . ],
        [5.6, 2.7, 4.2, 1.3],
        [5.7, . , 4.2, 1.2],
        [5.7, 2.9, 4.2, 1.3],
        [6.2, 2.9, 4.3, 1.3],
        [5.1, 2.5, . , 1.1],
        [5.7, 2.8, 4.1, 1.3],
        [6.3, 3.3, . , 2.5],
        [5.8, 2.7, 5.1, 1.9],
        [7.1, . , 5.9, 2.1],
        [6.3, 2.9, 5.6, 1.8],
        [6.5, . , 5.8, 2.2],
        [7.6, . , 6.6, 2.1],
        [4.9, 2.5, 4.5, 1.7],
        [7.3, 2.9, 6.3, 1.8],
        [6.7, 2.5, 5.8, 1.8],
        [7.2, 3.6, 6.1, 2.5],
        [6.5, 3.2, 5.1, . ],
        [6.4, 2.7, 5.3, 1.9],
        [6.8, . , 5.5, 2.1],
        [5.7, 2.5, . , . ],
        [5.8, 2.8, 5.1, 2.4],
        [6.4, 3.2, 5.3, 2.3],
        [6.5, . , 5.5, 1.8],
        [7.7, 3.8, 6.7, 2.2],
        [7.7, 2.6, 6.9, 2.3],
        [. , 2.2, . , 1.5],
        [6.9, 3.2, 5.7, 2.3],
        [5.6, 2.8, 4.9, . ],
        [7.7, 2.8, 6.7, . ],
        [6.3, 2.7, 4.9, 1.8],
        [6.7, 3.3, 5.7, 2.1],
        [7.2, 3.2, . , 1.8],
        [6.2, 2.8, 4.8, 1.8],
        [6.1, . , 4.9, 1.8],
        [6.4, 2.8, 5.6, 2.1],
        [7.2, . , 5.8, 1.6],
        [7.4, 2.8, 6.1, 1.9],
        [7.9, 3.8, 6.4, . ],
        [6.4, 2.8, 5.6, 2.2],
        [6.3, 2.8, 5.1, 1.5],
        [6.1, 2.6, 5.6, 1.4],
        [7.7, . , 6.1, 2.3],
        [6.3, 3.4, 5.6, 2.4],
        [6.4, 3.1, 5.5, 1.8],
        [. , . , 4.8, 1.8],
        [6.9, 3.1, 5.4, 2.1],
        [6.7, 3.1, 5.6, 2.4],
        [6.9, 3.1, 5.1, 2.3],
        [5.8, 2.7, 5.1, 1.9],
        [6.8, 3.2, 5.9, 2.3],
        [6.7, 3.3, 5.7, 2.5],
        [6.7, . , 5.2, 2.3],
        [6.3, 2.5, . , 1.9],
        [6.5, . , 5.2, . ],
        [6.2, 3.4, 5.4, 2.3],
        [5.9, . , 5.1, 1.8]]),
 'target': array([, , , , , , , , , , , , , , , , , , , , , ,
        , , , , , , , , , , , , , , , , , , , , , ,
        , , , , , , , , , , , , , , , , , , , , , ,
        , , , , , , , , , , , , , , , , , , , , , ,
        , , , , , , , , , , , , , , , , , , , , , ,
        , , , , , , , , , , , , , , , , , , , , , ,
        , , , , , , , , , , , , , , , , , ]),
 'target_names': array(['setosa', 'versicolor', 'virginica'], dtype='<U10'),
 'DESCR': 'Iris Plants Database\n====================\n\nNotes\n-----\nData Set Characteristics:\n    :Number of Instances: 150 (50 in each of three classes)\n    :Number of Attributes: 4 numeric, predictive attributes and the class\n    :Attribute Information:\n        - sepal length in cm\n        - sepal width in cm\n        - petal length in cm\n        - petal width in cm\n        - class:\n                - Iris-Setosa\n                - Iris-Versicolour\n                - Iris-Virginica\n    :Summary Statistics:\n\n    ============== ==== ==== ======= ===== ====================\n                    Min  Max   Mean    SD   Class Correlation\n    ============== ==== ==== ======= ===== ====================\n    sepal length:   4.3  7.9   5.84   0.83    0.7826\n    sepal width:    2.0  4.4   3.05   0.43   -0.4194\n    petal length:   1.0  6.9   3.76   1.76    0.9490  (high!)\n    petal width:    0.1  2.5   1.20  0.76     0.9565  (high!)\n    ============== ==== ==== ======= ===== ====================\n\n    :Missing Attribute Values: None\n    :Class Distribution: 33.3% for each of 3 classes.\n    :Creator: R.A. Fisher\n    :Donor: Michael Marshall (MARSHALL%PLU@io.arc.nasa.gov)\n    :Date: July, 1988\n\nThis is a copy of UCI ML iris datasets.\nhttp://archive.ics.uci.edu/ml/datasets/Iris\n\nThe famous Iris database, first used by Sir R.A Fisher\n\nThis is perhaps the best known database to be found in the\npattern recognition literature.  Fisher\'s paper is a classic in the field and\nis referenced frequently to this day.  (See Duda & Hart, for example.)  The\ndata set contains 3 classes of 50 instances each, where each class refers to a\ntype of iris plant.  One class is linearly separable from the other 2; the\nlatter are NOT linearly separable from each other.\n\nReferences\n----------\n   - Fisher,R.A. "The use of multiple measurements in taxonomic problems"\n     Annual Eugenics, 7, Part II, 179-188 (1936); also in "Contributions to\n     Mathematical Statistics" (John Wiley, NY, 1950).\n   - Duda,R.O., & Hart,P.E. (1973) Pattern Classification and Scene Analysis.\n     (Q327.D83) John Wiley & Sons.  ISBN 0-471-22361-1.  See page 218.\n   - Dasarathy, B.V. (1980) "Nosing Around the Neighborhood: A New System\n     Structure and Classification Rule for Recognition in Partially Exposed\n     Environments".  IEEE Transactions on Pattern Analysis and Machine\n     Intelligence, Vol. PAMI-2, No. 1, 67-71.\n   - Gates, G.W. (1972) "The Reduced Nearest Neighbor Rule".  IEEE Transactions\n     on Information Theory, May 1972, 431-433.\n   - See also: 1988 MLC Proceedings, 54-64.  Cheeseman et al"s AUTOCLASS II\n     conceptual clustering system finds 3 classes in the data.\n   - Many, many more ...\n',
 'feature_names': ['sepal length (cm)',
  'sepal width (cm)',
  'petal length (cm)',
  'petal width (cm)']}

iris

#提取样本数据
feature = iris['data']
target = iris['target']

#将样本数据进行随机打乱
np.random.seed(1)
np.random.shuffle(feature)
np.random.seed(1)
np.random.shuffle(target)

feature.shape #(150, 4)

#获取训练样本数据和测试样本数据
#训练数据
x_train = feature[:140]
y_train = target[:140]
#测试数据
x_test = feature[-10:]
y_test =target[-10:]

#实例化模型对象&训练模型
knn = KNeighborsClassifier(n_neighbors=10)
knn.fit(x_train,y_train)
knn.score(x_train,y_train)   #0.9857142857142858

print('预测分类：',knn.predict(x_test))
print('真实分类：',y_test)
预测分类： [0 2 1 2 0 1 2 1 1 0]
真实分类： [0 2 1 1 0 1 2 1 1 0]

　

# 选中最优的k值
k_list = []
s_list = []

for k in range(1,60):
    knn = KNeighborsClassifier(n_neighbors=k)
    knn.fit(x_train,y_train)
    s_list.append(s)
    k_list.append(k)

import matplot.pyplot as plt
plt.plot(k_list,s_list)