Python实现KNN
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KNN原理:
http://blog.csdn.net/jmydream/article/details/8644004
参考来源
https://my.oschina.net/fengcunhan/blog/101281
#!/usr/bin/python3# -*- coding: utf-8 -*-from numpy import *import operator# 这些数据的背后意义:某个妹纸想要找一个男朋友,她收集了婚恋网上面对她感兴趣男士的一些数据,# 第一个是一年的飞行里程,第二个是每年玩游戏的时间(10小时为单位),第三个是每年吃的冰淇淋量。# 第四个是结果:3表示很感兴趣,2表示感兴趣,1表示没兴趣class Classify: def __init__(self, trainData, trainlables): self.size = trainData.shape[0] self.trainData = self.normalization(trainData) self.trainlables = trainlables # 对数据进行归一化处理 # 归一化分为: # 线性函数归一化(Min-Max scaling):x = y / s y = x - x.min s = x.max - x.min # 0均值标准化(Z-score standardization):z = (x - μ) / σ,μ表示均值σ表示方差 # 0均值标准化要求原始数据的分布可以近似为高斯分布,否则归一化的效果会变得很糟糕。这里采用线性函数归一化 def normalization(self, trainData): # data m*n min与max用法相同 # data.min() 获取data中的最小值,一个数字 # data.min(0) data中每列最小的数据,1*n数组 # data.min(1) data中每行最小的数据,1*m数组 minary = trainData.min(0) maxary = trainData.max(0) interval = maxary - minary # tile(minary, (self.m, 1))表示构建一个self.m*1的矩阵。矩阵的每个元素是minary # a = [1, 2, 3] # tile(a, (2, 3))为[[1,2,3,1,2,3,1,2,3] [1,2,3,1,2,3,1,2,3]] Xnormal = trainData - tile(minary, (self.size, 1)) Xnormal = trainData / tile(interval, (self.size, 1)) return Xnormal # 预测分类 def predict(self, testData, testlables, k): testData = self.normalization(testData) size = len(testData) errorCount = 0.0 for i in range(size): result = self.classify(testData[i], k) if(result != testlables[i]): errorCount += 1.0 return errorCount / size def classify(self, inMat, k): # 计算欧式距离 diff = tile(inMat, (self.size, 1)) - self.trainData diffP = pow(diff.A, 2) distance = sqrt(diffP.sum(1)) # argsort函数返回的是数组值从小到大的索引值 index = distance.argsort() classCount = {} for i in range(k): l = self.trainlables[index[i]] # get(l, 0) 查找字典中key=l的value,如果没有该属性返回0 classCount[l] = classCount.get(l, 0) + 1 # key=operator.itemgetter(1) 定义函数key,获取对象的第1个域的值 sortedClassCount = sorted( classCount.items(), key=operator.itemgetter(1), reverse=True) return sortedClassCount[0][0]# 获取数据def readFile(filename): files = open(filename, "r", encoding="utf-8") trainData = [] lables = [] for line in files.readlines(): item = [float(i) for i in line.strip().split()] trainData.append(item[:- 1]) lables.append(item[- 1]) files.close() return mat(trainData), lables# -----------------------------------开始----------------------------# 用trainData作为训练,同时用trainData作为测试trainData, trainlables = readFile("/home/hadoop/Python/KNN/train.txt")model = Classify(trainData, trainlables)errorRate = model.predict(trainData, trainlables, 20)print("the error rate is :%f" % (errorRate))
数据:
40920 8.326976 0.953952 314488 7.153469 1.673904 226052 1.441871 0.805124 175136 13.147394 0.428964 138344 1.669788 0.134296 172993 10.141740 1.032955 135948 6.830792 1.213192 342666 13.276369 0.543880 367497 8.631577 0.749278 135483 12.273169 1.508053 350242 3.723498 0.831917 163275 8.385879 1.669485 15569 4.875435 0.728658 251052 4.680098 0.625224 177372 15.299570 0.331351 143673 1.889461 0.191283 161364 7.516754 1.269164 169673 14.239195 0.261333 115669 0.000000 1.250185 228488 10.528555 1.304844 36487 3.540265 0.822483 237708 2.991551 0.833920 122620 5.297865 0.638306 228782 6.593803 0.187108 319739 2.816760 1.686209 236788 12.458258 0.649617 35741 0.000000 1.656418 228567 9.968648 0.731232 36808 1.364838 0.640103 241611 0.230453 1.151996 136661 11.865402 0.882810 343605 0.120460 1.352013 115360 8.545204 1.340429 363796 5.856649 0.160006 110743 9.665618 0.778626 270808 9.778763 1.084103 172011 4.932976 0.632026 15914 2.216246 0.587095 214851 14.305636 0.632317 333553 12.591889 0.686581 344952 3.424649 1.004504 117934 0.000000 0.147573 227738 8.533823 0.205324 329290 9.829528 0.238620 342330 11.492186 0.263499 336429 3.570968 0.832254 139623 1.771228 0.207612 132404 3.513921 0.991854 127268 4.398172 0.975024 15477 4.276823 1.174874 214254 5.946014 1.614244 268613 13.798970 0.724375 141539 10.393591 1.663724 37917 3.007577 0.297302 221331 1.031938 0.486174 28338 4.751212 0.064693 25176 3.692269 1.655113 218983 10.448091 0.267652 368837 10.585786 0.329557 113438 1.604501 0.069064 248849 3.679497 0.961466 112285 3.795146 0.696694 27826 2.531885 1.659173 25565 9.733340 0.977746 210346 6.093067 1.413798 21823 7.712960 1.054927 29744 11.470364 0.760461 316857 2.886529 0.934416 239336 10.054373 1.138351 365230 9.972470 0.881876 12463 2.335785 1.366145 227353 11.375155 1.528626 316191 0.000000 0.605619 212258 4.126787 0.357501 242377 6.319522 1.058602 125607 8.680527 0.086955 377450 14.856391 1.129823 158732 2.454285 0.222380 146426 7.292202 0.548607 332688 8.745137 0.857348 364890 8.579001 0.683048 18554 2.507302 0.869177 228861 11.415476 1.505466 342050 4.838540 1.680892 132193 10.339507 0.583646 364895 6.573742 1.151433 12355 6.539397 0.462065 20 2.209159 0.723567 270406 11.196378 0.836326 157399 4.229595 0.128253 141732 9.505944 0.005273 311429 8.652725 1.348934 375270 17.101108 0.490712 15459 7.871839 0.717662 273520 8.262131 1.361646 140279 9.015635 1.658555 321540 9.215351 0.806762 317694 6.375007 0.033678 222329 2.262014 1.022169 146570 5.677110 0.709469 142403 11.293017 0.207976 333654 6.590043 1.353117 19171 4.711960 0.194167 228122 8.768099 1.108041 334095 11.502519 0.545097 31774 4.682812 0.578112 240131 12.446578 0.300754 313994 12.908384 1.657722 377064 12.601108 0.974527 111210 3.929456 0.025466 26122 9.751503 1.182050 315341 3.043767 0.888168 244373 4.391522 0.807100 128454 11.695276 0.679015 363771 7.879742 0.154263 19217 5.613163 0.933632 269076 9.140172 0.851300 124489 4.258644 0.206892 116871 6.799831 1.221171 239776 8.752758 0.484418 35901 1.123033 1.180352 240987 10.833248 1.585426 37479 3.051618 0.026781 238768 5.308409 0.030683 34933 1.841792 0.028099 232311 2.261978 1.605603 126501 11.573696 1.061347 337433 8.038764 1.083910 323503 10.734007 0.103715 368607 9.661909 0.350772 127742 9.005850 0.548737 311303 0.000000 0.539131 20 5.757140 1.062373 232729 9.164656 1.624565 324619 1.318340 1.436243 142414 14.075597 0.695934 320210 10.107550 1.308398 333225 7.960293 1.219760 354483 6.317292 0.018209 118475 12.664194 0.595653 333926 2.906644 0.581657 143865 2.388241 0.913938 126547 6.024471 0.486215 344404 7.226764 1.255329 316674 4.183997 1.275290 28123 11.850211 1.096981 342747 11.661797 1.167935 356054 3.574967 0.494666 110933 0.000000 0.107475 218121 7.937657 0.904799 311272 3.365027 1.014085 216297 0.000000 0.367491 228168 13.860672 1.293270 340963 10.306714 1.211594 331685 7.228002 0.670670 355164 4.508740 1.036192 117595 0.366328 0.163652 21862 3.299444 0.575152 257087 0.573287 0.607915 163082 9.183738 0.012280 151213 7.842646 1.060636 36487 4.750964 0.558240 24805 11.438702 1.556334 330302 8.243063 1.122768 368680 7.949017 0.271865 117591 7.875477 0.227085 274391 9.569087 0.364856 137217 7.750103 0.869094 342814 0.000000 1.515293 114738 3.396030 0.633977 219896 11.916091 0.025294 314673 0.460758 0.689586 232011 13.087566 0.476002 358736 4.589016 1.672600 154744 8.397217 1.534103 129482 5.562772 1.689388 127698 10.905159 0.619091 311443 1.311441 1.169887 256117 10.647170 0.980141 339514 0.000000 0.481918 126627 8.503025 0.830861 316525 0.436880 1.395314 224368 6.127867 1.102179 122160 12.112492 0.359680 36030 1.264968 1.141582 26468 6.067568 1.327047 222945 8.010964 1.681648 318520 3.791084 0.304072 234914 11.773195 1.262621 36121 8.339588 1.443357 238063 2.563092 1.464013 123410 5.954216 0.953782 135073 9.288374 0.767318 352914 3.976796 1.043109 116801 8.585227 1.455708 39533 1.271946 0.796506 216721 0.000000 0.242778 25832 0.000000 0.089749 244591 11.521298 0.300860 310143 1.139447 0.415373 221609 5.699090 1.391892 223817 2.449378 1.322560 115640 0.000000 1.228380 28847 3.168365 0.053993 250939 10.428610 1.126257 328521 2.943070 1.446816 132901 10.441348 0.975283 342850 12.478764 1.628726 313499 5.856902 0.363883 240345 2.476420 0.096075 143547 1.826637 0.811457 170758 4.324451 0.328235 119780 1.376085 1.178359 244484 5.342462 0.394527 154462 11.835521 0.693301 320085 12.423687 1.424264 342291 12.161273 0.071131 347550 8.148360 1.649194 311938 1.531067 1.549756 240699 3.200912 0.309679 170908 8.862691 0.530506 173989 6.370551 0.369350 111872 2.468841 0.145060 248463 11.054212 0.141508 315987 2.037080 0.715243 270036 13.364030 0.549972 132967 10.249135 0.192735 363249 10.464252 1.669767 142795 9.424574 0.013725 314459 4.458902 0.268444 219973 0.000000 0.575976 25494 9.686082 1.029808 367902 13.649402 1.052618 125621 13.181148 0.273014 327545 3.877472 0.401600 158656 1.413952 0.451380 17327 4.248986 1.430249 264555 8.779183 0.845947 18998 4.156252 0.097109 211752 5.580018 0.158401 276319 15.040440 1.366898 127665 12.793870 1.307323 367417 3.254877 0.669546 121808 10.725607 0.588588 315326 8.256473 0.765891 220057 8.033892 1.618562 379341 10.702532 0.204792 115636 5.062996 1.132555 235602 10.772286 0.668721 328544 1.892354 0.837028 157663 1.019966 0.372320 178727 15.546043 0.729742 168255 11.638205 0.409125 114964 3.427886 0.975616 221835 11.246174 1.475586 37487 0.000000 0.645045 28700 0.000000 1.424017 226226 8.242553 0.279069 365899 8.700060 0.101807 16543 0.812344 0.260334 246556 2.448235 1.176829 171038 13.230078 0.616147 147657 0.236133 0.340840 119600 11.155826 0.335131 337422 11.029636 0.505769 31363 2.901181 1.646633 226535 3.924594 1.143120 147707 2.524806 1.292848 138055 3.527474 1.449158 16286 3.384281 0.889268 210747 0.000000 1.107592 244883 11.898890 0.406441 356823 3.529892 1.375844 168086 11.442677 0.696919 170242 10.308145 0.422722 111409 8.540529 0.727373 267671 7.156949 1.691682 161238 0.720675 0.847574 117774 0.229405 1.038603 253376 3.399331 0.077501 130930 6.157239 0.580133 128987 1.239698 0.719989 113655 6.036854 0.016548 27227 5.258665 0.933722 240409 12.393001 1.571281 313605 9.627613 0.935842 226400 11.130453 0.597610 313491 8.842595 0.349768 330232 10.690010 1.456595 343253 5.714718 1.674780 355536 3.052505 1.335804 18807 0.000000 0.059025 225783 9.945307 1.287952 322812 2.719723 1.142148 177826 11.154055 1.608486 138172 2.687918 0.660836 131676 10.037847 0.962245 374038 12.404762 1.112080 144738 10.237305 0.633422 317410 4.745392 0.662520 25688 4.639461 1.569431 236642 3.149310 0.639669 129956 13.406875 1.639194 360350 6.068668 0.881241 123758 9.477022 0.899002 325780 3.897620 0.560201 211342 5.463615 1.203677 236109 3.369267 1.575043 114292 5.234562 0.825954 211160 0.000000 0.722170 223762 12.979069 0.504068 339567 5.376564 0.557476 125647 13.527910 1.586732 314814 2.196889 0.784587 273590 10.691748 0.007509 135187 1.659242 0.447066 149459 8.369667 0.656697 331657 13.157197 0.143248 36259 8.199667 0.908508 233101 4.441669 0.439381 327107 9.846492 0.644523 317824 0.019540 0.977949 243536 8.253774 0.748700 367705 6.038620 1.509646 135283 6.091587 1.694641 371308 8.986820 1.225165 131054 11.508473 1.624296 352387 8.807734 0.713922 340328 0.000000 0.816676 134844 8.889202 1.665414 311607 3.178117 0.542752 264306 7.013795 0.139909 132721 9.605014 0.065254 333170 1.230540 1.331674 137192 10.412811 0.890803 313089 0.000000 0.567161 266491 9.699991 0.122011 115941 0.000000 0.061191 24272 4.455293 0.272135 248812 3.020977 1.502803 128818 8.099278 0.216317 335394 1.157764 1.603217 171791 10.105396 0.121067 140668 11.230148 0.408603 339580 9.070058 0.011379 311786 0.566460 0.478837 219251 0.000000 0.487300 256594 8.956369 1.193484 354495 1.523057 0.620528 111844 2.749006 0.169855 245465 9.235393 0.188350 331033 10.555573 0.403927 316633 6.956372 1.519308 213887 0.636281 1.273984 252603 3.574737 0.075163 172000 9.032486 1.461809 168497 5.958993 0.023012 135135 2.435300 1.211744 126397 10.539731 1.638248 37313 7.646702 0.056513 291273 20.919349 0.644571 124743 1.424726 0.838447 131690 6.748663 0.890223 315432 2.289167 0.114881 258394 5.548377 0.402238 133962 6.057227 0.432666 131442 10.828595 0.559955 331044 11.318160 0.271094 329938 13.265311 0.633903 39875 0.000000 1.496715 251542 6.517133 0.402519 311878 4.934374 1.520028 269241 10.151738 0.896433 137776 2.425781 1.559467 168997 9.778962 1.195498 167416 12.219950 0.657677 159225 7.394151 0.954434 129138 8.518535 0.742546 35962 2.798700 0.662632 210847 0.637930 0.617373 270527 10.750490 0.097415 19610 0.625382 0.140969 264734 10.027968 0.282787 125941 9.817347 0.364197 32763 0.646828 1.266069 255601 3.347111 0.914294 131128 11.816892 0.193798 35181 0.000000 1.480198 269982 10.945666 0.993219 152440 10.244706 0.280539 357350 2.579801 1.149172 157869 2.630410 0.098869 156557 11.746200 1.695517 342342 8.104232 1.326277 315560 12.409743 0.790295 334826 12.167844 1.328086 38569 3.198408 0.299287 277623 16.055513 0.541052 178184 7.138659 0.158481 17036 4.831041 0.761419 269616 10.082890 1.373611 121546 10.066867 0.788470 336715 8.129538 0.329913 320522 3.012463 1.138108 242349 3.720391 0.845974 19037 0.773493 1.148256 226728 10.962941 1.037324 3587 0.177621 0.162614 248915 3.085853 0.967899 19824 8.426781 0.202558 24135 1.825927 1.128347 29666 2.185155 1.010173 259333 7.184595 1.261338 136198 0.000000 0.116525 134909 8.901752 1.033527 347516 2.451497 1.358795 155807 3.213631 0.432044 114036 3.974739 0.723929 242856 9.601306 0.619232 364007 8.363897 0.445341 159428 6.381484 1.365019 113730 0.000000 1.403914 241740 9.609836 1.438105 363546 9.904741 0.985862 130417 7.185807 1.489102 369636 5.466703 1.216571 164660 0.000000 0.915898 114883 4.575443 0.535671 27965 3.277076 1.010868 268620 10.246623 1.239634 18738 2.341735 1.060235 27544 3.201046 0.498843 26377 6.066013 0.120927 236842 8.829379 0.895657 381046 15.833048 1.568245 167736 13.516711 1.220153 132492 0.664284 1.116755 139299 6.325139 0.605109 377289 8.677499 0.344373 133835 8.188005 0.964896 371890 9.414263 0.384030 132054 9.196547 1.138253 338579 10.202968 0.452363 355984 2.119439 1.481661 172694 13.635078 0.858314 142299 0.083443 0.701669 126635 9.149096 1.051446 38579 1.933803 1.374388 237302 14.115544 0.676198 322878 8.933736 0.943352 34364 2.661254 0.946117 24985 0.988432 1.305027 237068 2.063741 1.125946 141137 2.220590 0.690754 167759 6.424849 0.806641 111831 1.156153 1.613674 234502 3.032720 0.601847 14088 3.076828 0.952089 215199 0.000000 0.318105 217309 7.750480 0.554015 342816 10.958135 1.482500 343751 10.222018 0.488678 358335 2.367988 0.435741 175039 7.686054 1.381455 142878 11.464879 1.481589 342770 11.075735 0.089726 38848 3.543989 0.345853 231340 8.123889 1.282880 341413 4.331769 0.754467 312731 0.120865 1.211961 222447 6.116109 0.701523 333564 7.474534 0.505790 348907 8.819454 0.649292 38762 6.802144 0.615284 246696 12.666325 0.931960 336851 8.636180 0.399333 367639 11.730991 1.289833 1171 8.132449 0.039062 226674 10.296589 1.496144 38739 7.583906 1.005764 266668 9.777806 0.496377 168732 8.833546 0.513876 169995 4.907899 1.518036 182008 8.362736 1.285939 125054 9.084726 1.606312 333085 14.164141 0.560970 341379 9.080683 0.989920 339417 6.522767 0.038548 312556 3.690342 0.462281 239432 3.563706 0.242019 138010 1.065870 1.141569 169306 6.683796 1.456317 138000 1.712874 0.243945 146321 13.109929 1.280111 366293 11.327910 0.780977 122730 4.545711 1.233254 15952 3.367889 0.468104 272308 8.326224 0.567347 160338 8.978339 1.442034 113301 5.655826 1.582159 227884 8.855312 0.570684 311188 6.649568 0.544233 256796 3.966325 0.850410 18571 1.924045 1.664782 24914 6.004812 0.280369 210784 0.000000 0.375849 239296 9.923018 0.092192 313113 2.389084 0.119284 270204 13.663189 0.133251 146813 11.434976 0.321216 311697 0.358270 1.292858 244183 9.598873 0.223524 32225 6.375275 0.608040 229066 11.580532 0.458401 34245 5.319324 1.598070 234379 4.324031 1.603481 144441 2.358370 1.273204 12022 0.000000 1.182708 226866 12.824376 0.890411 357070 1.587247 1.456982 132932 8.510324 1.520683 351967 10.428884 1.187734 344432 8.346618 0.042318 367066 7.541444 0.809226 117262 2.540946 1.583286 279728 9.473047 0.692513 114259 0.352284 0.474080 26122 0.000000 0.589826 276879 12.405171 0.567201 111426 4.126775 0.871452 22493 0.034087 0.335848 219910 1.177634 0.075106 210939 0.000000 0.479996 217716 0.994909 0.611135 231390 11.053664 1.180117 320375 0.000000 1.679729 226309 2.495011 1.459589 133484 11.516831 0.001156 345944 9.213215 0.797743 34249 5.332865 0.109288 26089 0.000000 1.689771 27513 0.000000 1.126053 227862 12.640062 1.690903 339038 2.693142 1.317518 119218 3.328969 0.268271 262911 7.193166 1.117456 177758 6.615512 1.521012 127940 8.000567 0.835341 32194 4.017541 0.512104 237072 13.245859 0.927465 315585 5.970616 0.813624 225577 11.668719 0.886902 38777 4.283237 1.272728 229016 10.742963 0.971401 321910 12.326672 1.592608 312916 0.000000 0.344622 210976 0.000000 0.922846 279065 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1.645301 171142 10.442780 0.335870 137653 3.834509 1.346121 176839 10.998587 0.584555 19916 2.695935 1.512111 238889 3.356646 0.324230 139075 14.677836 0.793183 348071 1.551934 0.130902 17275 2.464739 0.223502 241804 1.533216 1.007481 135665 12.473921 0.162910 367956 6.491596 0.032576 141892 10.506276 1.510747 338844 4.380388 0.748506 174197 13.670988 1.687944 114201 8.317599 0.390409 23908 0.000000 0.556245 22459 0.000000 0.290218 232027 10.095799 1.188148 312870 0.860695 1.482632 29880 1.557564 0.711278 272784 10.072779 0.756030 117521 0.000000 0.431468 250283 7.140817 0.883813 333536 11.384548 1.438307 39452 3.214568 1.083536 237457 11.720655 0.301636 317724 6.374475 1.475925 343869 5.749684 0.198875 3264 3.871808 0.552602 225736 8.336309 0.636238 339584 9.710442 1.503735 331246 1.532611 1.433898 149567 9.785785 0.984614 37052 2.633627 1.097866 235493 9.238935 0.494701 310986 1.205656 1.398803 249508 3.124909 1.670121 15734 7.935489 1.585044 265479 12.746636 1.560352 177268 10.732563 0.545321 128490 3.977403 0.766103 113546 4.194426 0.450663 237166 9.610286 0.142912 316381 4.797555 1.260455 210848 1.615279 0.093002 235405 4.614771 1.027105 115917 0.000000 1.369726 26131 0.608457 0.512220 267432 6.558239 0.667579 130354 12.315116 0.197068 369696 7.014973 1.494616 133481 8.822304 1.194177 343075 10.086796 0.570455 338343 7.241614 1.661627 314318 4.602395 1.511768 25367 7.434921 0.079792 237894 10.467570 1.595418 336172 9.948127 0.003663 340123 2.478529 1.568987 110976 5.938545 0.878540 212705 0.000000 0.948004 212495 5.559181 1.357926 235681 9.776654 0.535966 346202 3.092056 0.490906 111505 0.000000 1.623311 222834 4.459495 0.538867 149901 8.334306 1.646600 371932 11.226654 0.384686 113279 3.904737 1.597294 249112 7.038205 1.211329 377129 9.836120 1.054340 137447 1.990976 0.378081 162397 9.005302 0.485385 10 1.772510 1.039873 215476 0.458674 0.819560 240625 10.003919 0.231658 336706 0.520807 1.476008 128580 10.678214 1.431837 325862 4.425992 1.363842 163488 12.035355 0.831222 133944 10.606732 1.253858 330099 1.568653 0.684264 113725 2.545434 0.024271 236768 10.264062 0.982593 364656 9.866276 0.685218 114927 0.142704 0.057455 243231 9.853270 1.521432 366087 6.596604 1.653574 119806 2.602287 1.321481 241081 10.411776 0.664168 310277 7.083449 0.622589 27014 2.080068 1.254441 217275 0.522844 1.622458 231600 10.362000 1.544827 3
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