copy of temp.train.txt

一个matlab的工具包,里面包括一些分类器 例如 KNN KMEAN SVM NETLAB 等等有很多.

1 1:0.32999 2:0.23117 3:0.71963 4:0.46896 5:0.5183 6:0.40032 7:0.26014 8:0.35161 9:0.69534 10:0.65606 11:0.58732 12:0.50382 13:0.34947 14:0.402 15:0.71822 16:0.60495 17:0.50755 18:0.43251 19:0.31906 20:0.22243 21:0.71627 22:0.5003 23:0.47305 24:0.41401 25:0.38795 26:0.23523 27:0.62597 28:0.439 29:0.40924 30:0.33893 31:0.28013 32:0.32003 33:0.62972 34:0.4766 35:0.44826 36:0.45975 37:0.18886 38:0.40986 39:0.65539 40:0.84174 41:0.87505 42:0.80383 43:0.33616 44:0.1567 45:0.59432 46:0.35317 47:0.57167 48:0.30179 49:0.26344 50:0.27973 51:0.72535 52:0.52362 53:0.81216 54:0.81424 55:0.39909 56:0.33989 57:0.57733 58:0.3231 59:0.60912 60:0.45977 61:0.32798 62:0.23963 63:0.55377 64:0.46771 65:0.39656 66:0.44416 67:0.22508 68:0.32298 69:0.66956 70:0.82704 71:0.8545 72:0.78503 73:0.34765 74:0.19678 75:0.58076 76:0.54553 77:0.50662 78:0.43616 79:0.32275 80:0.21187 81:0.58445 82:0.38296 83:0.53992 84:0.42913 85:0.34011 86:0.19256 87:0.56785 88:0.39939 89:0.54553 90:0.38476 91:0.33715 92:0.50909 93:0.38323 94:0.48735 95:0.28093 96:0.42417 97:0.28302 98:0.58647 99:0.4554 100:0.37329 101:0.84172 102:1.3428 103:0.31673 104:0.39266 105:0.36832 106:0.42433 107:0.3907 108:0.43733 109:0.29271 110:0.27941 111:0.49551 112:0.58013 113:0.39251 114:0.52432 115:0.23254 116:0.31016 117:0.55299 118:0.63997 119:0.44484 120:0.58168 121:0.37278 122:0.50183 123:0.60608 124:0.39755 125:0.46793 126:0.3955 127:0.3564 128:0.55402 129:0.59144 130:0.3955 131:0.50091 132:0.37211 133:0.34397 134:0.60747 135:0.61402 136:0.4369 137:0.48101 138:0.40317 139:0.34841 140:0.68955 141:0.67816 142:0.50782 143:0.49428 144:0.40167 145:0.34216 146:0.66566 147:0.69428 148:0.57915 149:0.51666 150:0.42299 151:1 152:10.298 153:5625 154:7.6941 155:6.7472 156:7.8125 157:6.9839 158:10.0616 159:10.535 160:11.8371 161:9.8248 162:14.2045 163:15.625 164:14.2045 165:11.6004 166:10.6534 167:9.1146 168:10.2983 169:9.4697 170:14.678 171:23.2008 172:42.8504 173:12.1922 174:8.9962 175:9.1146 176:6.7472 177:9.233 178:9.4697 179:8.4044 180:11.8371 181:11.2453 182:7.9309 183:9.3513 184:5.6818 185:6.9839 186:7.1023 187:5.6818 188:6.392 189:9.8248 190:7.339 191:8.5227 192:7.6941 193:8.286 194:8.7595 195:12.9025 196:12.1922 197:14.5597 198:16.2169 199:14.5597 200:13.1392 201:10.535 202:9.3513 203:9.4697 204:8.6411 205:9.3513 206:13.4943 207:18.3475 208:19.1761 209:12.0739 210:9.1146 211:7.4574 212:7.339 213:8.286 214:8.6411 215:12.7841 216:12.1922 217:14.9148 218:10.1799 219:7.5758 220:5.4451 221:7.6941 222:4.3797 223:5.5634 224:7.9309 225:7.1023 
4 1:0.29171 2:0.38675 3:0.52788 4:0.59546 5:0.58569 6:0.62549 7:0.32952 8:0.38251 9:0.45547 10:0.50824 11:0.61575 12:0.55072 13:0.37833 14:0.35792 15:0.29089 16:0.39346 17:0.51291 18:0.52652 19:0.35725 20:0.37811 21:0.2638 22:0.3984 23:0.39351 24:0.70559 25:0.25844 26:0.39988 27:0.29784 28:0.4595 29:0.40275 30:0.66421 31:0.26986 32:0.41635 33:0.50304 34:0.5456 35:0.61882 36:0.72307 37:0.23028 38:0.38778 39:0.42954 40:0.49951 41:0.66784 42:0.61164 43:0.20713 44:0.31758 45:0.37481 46:0.48684 47:0.53321 48:0.63597 49:0.31097 50:0.49828 51:0.33361 52:0.58293 53:0.41265 54:0.64289 55:0.29125 56:0.25016 57:0.29561 58:0.41161 59:0.46214 60:0.57207 61:0.31803 62:0.32244 63:0.63171 64:0.60006 65:0.741 66:0.72616 67:0.21253 68:0.52334 69:0.48409 70:0.80605 71:0.72386 72:1.1902 73:0.25452 74:0.24014 75:0.32607 76:0.37253 77:0.58214 78:0.50206 79:0.44905 80:0.38042 81:0.26491 82:0.41131 83:0.55285 84:0.5487 85:0.41717 86:0.43879 87:0.25497 88:0.4281 89:0.66942 90:0.64266 91:0.4495 92:0.95641 93:0.42611 94:0.70862 95:0.45971 96:0.65168 97:0.25122 98:0.32894 99:0.4953 100:0.63608 101:0.70595 102:0.92929 103:0.30742 104:0.36128 105:0.31245 106:0.41754 107:0.72167 108:0.54066 109:0.45311 110:0.4098 111:0.28587 112:0.40255 113:0.51248 114:0.55713 115:0.35139 116:0.33627 117:0.2533 118:0.39461 119:0.5185 120:0.46832 121:0.37973 122:0.62972 123:0.57437 124:0.47617 125:0.49115 126:0.51293 127:0.32695 128:0.74002 129:0.60779 130:0.53149 131:0.59805 132:0.53831 133:0.36543 134:0.68487 135:0.64836 136:0.54552 137:0.60627 138:0.67579 139:0.37596 140:0.74037 141:0.62525 142:0.5475 143:0.60366 144:0.59226 145:0.33472 146:0.681 147:0.59745 148:0.55976 149:0.64248 150:0.55755 154:5.5957 155:6.4566 156:6.5642 157:7.6403 158:9.4697 159:10.223 160:9.1469 161:11.7295 162:12.0523 163:13.7741 164:15.2806 165:11.7295 166:16.6796 167:13.8817 168:15.7111 169:15.9263 170:22.3829 171:32.7135 172:46.4876 173:18.8318 174:15.6035 175:13.7741 176:12.8056 177:10.0077 178:14.635 179:18.509 180:14.8502 181:13.5589 182:12.3752 183:9.3621 184:8.3936 185:8.1784 186:6.8871 187:6.1338 188:5.3805 189:6.7794 190:7.2099 191:7.3175 192:5.1653 193:8.0708 194:10.4382 195:10.4382 196:10.5458 197:9.4697 198:13.3437 199:12.8056 200:15.0654 201:14.5274 202:14.9578 203:14.3122 204:16.4644 205:15.2806 206:15.3883 207:15.2806 208:11.9447 209:11.6219 210:7.3175 211:11.8371 212:10.6534 213:9.3621 214:11.5143 215:10.761 216:13.6665 217:12.16 218:11.5143 219:10.761 220:7.1023 221:7.1023 222:5.811 223:8.0708 224:5.9186 225:6.6718 
5 1:0.58927 2:0.74451 3:0.39336 4:0.49544 5:0.27861 6:0.40621 7:0.36955 8:0.60208 9:0.46374 10:0.51488 11:0.42363 12:0.61993 13:0.51964 14:0.38918 15:0.43716 16:0.44589 17:0.41361 18:0.67601 19:0.44271 20:0.40757 21:0.36719 22:0.3525 23:0.34325 24:0.38753 25:0.33489 26:0.45298 27:0.47738 28:0.52262