library(mlbench)
## Warning: package 'mlbench' was built under R version 4.3.3
library(caret)
## Warning: package 'caret' was built under R version 4.3.3
## Loading required package: ggplot2
## Warning: package 'ggplot2' was built under R version 4.3.2
## Loading required package: lattice
data(PimaIndiansDiabetes)
dataset <- PimaIndiansDiabetes
dataset
## pregnant glucose pressure triceps insulin mass pedigree age diabetes
## 1 6 148 72 35 0 33.6 0.627 50 pos
## 2 1 85 66 29 0 26.6 0.351 31 neg
## 3 8 183 64 0 0 23.3 0.672 32 pos
## 4 1 89 66 23 94 28.1 0.167 21 neg
## 5 0 137 40 35 168 43.1 2.288 33 pos
## 6 5 116 74 0 0 25.6 0.201 30 neg
## 7 3 78 50 32 88 31.0 0.248 26 pos
## 8 10 115 0 0 0 35.3 0.134 29 neg
## 9 2 197 70 45 543 30.5 0.158 53 pos
## 10 8 125 96 0 0 0.0 0.232 54 pos
## 11 4 110 92 0 0 37.6 0.191 30 neg
## 12 10 168 74 0 0 38.0 0.537 34 pos
## 13 10 139 80 0 0 27.1 1.441 57 neg
## 14 1 189 60 23 846 30.1 0.398 59 pos
## 15 5 166 72 19 175 25.8 0.587 51 pos
## 16 7 100 0 0 0 30.0 0.484 32 pos
## 17 0 118 84 47 230 45.8 0.551 31 pos
## 18 7 107 74 0 0 29.6 0.254 31 pos
## 19 1 103 30 38 83 43.3 0.183 33 neg
## 20 1 115 70 30 96 34.6 0.529 32 pos
## 21 3 126 88 41 235 39.3 0.704 27 neg
## 22 8 99 84 0 0 35.4 0.388 50 neg
## 23 7 196 90 0 0 39.8 0.451 41 pos
## 24 9 119 80 35 0 29.0 0.263 29 pos
## 25 11 143 94 33 146 36.6 0.254 51 pos
## 26 10 125 70 26 115 31.1 0.205 41 pos
## 27 7 147 76 0 0 39.4 0.257 43 pos
## 28 1 97 66 15 140 23.2 0.487 22 neg
## 29 13 145 82 19 110 22.2 0.245 57 neg
## 30 5 117 92 0 0 34.1 0.337 38 neg
## 31 5 109 75 26 0 36.0 0.546 60 neg
## 32 3 158 76 36 245 31.6 0.851 28 pos
## 33 3 88 58 11 54 24.8 0.267 22 neg
## 34 6 92 92 0 0 19.9 0.188 28 neg
## 35 10 122 78 31 0 27.6 0.512 45 neg
## 36 4 103 60 33 192 24.0 0.966 33 neg
## 37 11 138 76 0 0 33.2 0.420 35 neg
## 38 9 102 76 37 0 32.9 0.665 46 pos
## 39 2 90 68 42 0 38.2 0.503 27 pos
## 40 4 111 72 47 207 37.1 1.390 56 pos
## 41 3 180 64 25 70 34.0 0.271 26 neg
## 42 7 133 84 0 0 40.2 0.696 37 neg
## 43 7 106 92 18 0 22.7 0.235 48 neg
## 44 9 171 110 24 240 45.4 0.721 54 pos
## 45 7 159 64 0 0 27.4 0.294 40 neg
## 46 0 180 66 39 0 42.0 1.893 25 pos
## 47 1 146 56 0 0 29.7 0.564 29 neg
## 48 2 71 70 27 0 28.0 0.586 22 neg
## 49 7 103 66 32 0 39.1 0.344 31 pos
## 50 7 105 0 0 0 0.0 0.305 24 neg
## 51 1 103 80 11 82 19.4 0.491 22 neg
## 52 1 101 50 15 36 24.2 0.526 26 neg
## 53 5 88 66 21 23 24.4 0.342 30 neg
## 54 8 176 90 34 300 33.7 0.467 58 pos
## 55 7 150 66 42 342 34.7 0.718 42 neg
## 56 1 73 50 10 0 23.0 0.248 21 neg
## 57 7 187 68 39 304 37.7 0.254 41 pos
## 58 0 100 88 60 110 46.8 0.962 31 neg
## 59 0 146 82 0 0 40.5 1.781 44 neg
## 60 0 105 64 41 142 41.5 0.173 22 neg
## 61 2 84 0 0 0 0.0 0.304 21 neg
## 62 8 133 72 0 0 32.9 0.270 39 pos
## 63 5 44 62 0 0 25.0 0.587 36 neg
## 64 2 141 58 34 128 25.4 0.699 24 neg
## 65 7 114 66 0 0 32.8 0.258 42 pos
## 66 5 99 74 27 0 29.0 0.203 32 neg
## 67 0 109 88 30 0 32.5 0.855 38 pos
## 68 2 109 92 0 0 42.7 0.845 54 neg
## 69 1 95 66 13 38 19.6 0.334 25 neg
## 70 4 146 85 27 100 28.9 0.189 27 neg
## 71 2 100 66 20 90 32.9 0.867 28 pos
## 72 5 139 64 35 140 28.6 0.411 26 neg
## 73 13 126 90 0 0 43.4 0.583 42 pos
## 74 4 129 86 20 270 35.1 0.231 23 neg
## 75 1 79 75 30 0 32.0 0.396 22 neg
## 76 1 0 48 20 0 24.7 0.140 22 neg
## 77 7 62 78 0 0 32.6 0.391 41 neg
## 78 5 95 72 33 0 37.7 0.370 27 neg
## 79 0 131 0 0 0 43.2 0.270 26 pos
## 80 2 112 66 22 0 25.0 0.307 24 neg
## 81 3 113 44 13 0 22.4 0.140 22 neg
## 82 2 74 0 0 0 0.0 0.102 22 neg
## 83 7 83 78 26 71 29.3 0.767 36 neg
## 84 0 101 65 28 0 24.6 0.237 22 neg
## 85 5 137 108 0 0 48.8 0.227 37 pos
## 86 2 110 74 29 125 32.4 0.698 27 neg
## 87 13 106 72 54 0 36.6 0.178 45 neg
## 88 2 100 68 25 71 38.5 0.324 26 neg
## 89 15 136 70 32 110 37.1 0.153 43 pos
## 90 1 107 68 19 0 26.5 0.165 24 neg
## 91 1 80 55 0 0 19.1 0.258 21 neg
## 92 4 123 80 15 176 32.0 0.443 34 neg
## 93 7 81 78 40 48 46.7 0.261 42 neg
## 94 4 134 72 0 0 23.8 0.277 60 pos
## 95 2 142 82 18 64 24.7 0.761 21 neg
## 96 6 144 72 27 228 33.9 0.255 40 neg
## 97 2 92 62 28 0 31.6 0.130 24 neg
## 98 1 71 48 18 76 20.4 0.323 22 neg
## 99 6 93 50 30 64 28.7 0.356 23 neg
## 100 1 122 90 51 220 49.7 0.325 31 pos
## 101 1 163 72 0 0 39.0 1.222 33 pos
## 102 1 151 60 0 0 26.1 0.179 22 neg
## 103 0 125 96 0 0 22.5 0.262 21 neg
## 104 1 81 72 18 40 26.6 0.283 24 neg
## 105 2 85 65 0 0 39.6 0.930 27 neg
## 106 1 126 56 29 152 28.7 0.801 21 neg
## 107 1 96 122 0 0 22.4 0.207 27 neg
## 108 4 144 58 28 140 29.5 0.287 37 neg
## 109 3 83 58 31 18 34.3 0.336 25 neg
## 110 0 95 85 25 36 37.4 0.247 24 pos
## 111 3 171 72 33 135 33.3 0.199 24 pos
## 112 8 155 62 26 495 34.0 0.543 46 pos
## 113 1 89 76 34 37 31.2 0.192 23 neg
## 114 4 76 62 0 0 34.0 0.391 25 neg
## 115 7 160 54 32 175 30.5 0.588 39 pos
## 116 4 146 92 0 0 31.2 0.539 61 pos
## 117 5 124 74 0 0 34.0 0.220 38 pos
## 118 5 78 48 0 0 33.7 0.654 25 neg
## 119 4 97 60 23 0 28.2 0.443 22 neg
## 120 4 99 76 15 51 23.2 0.223 21 neg
## 121 0 162 76 56 100 53.2 0.759 25 pos
## 122 6 111 64 39 0 34.2 0.260 24 neg
## 123 2 107 74 30 100 33.6 0.404 23 neg
## 124 5 132 80 0 0 26.8 0.186 69 neg
## 125 0 113 76 0 0 33.3 0.278 23 pos
## 126 1 88 30 42 99 55.0 0.496 26 pos
## 127 3 120 70 30 135 42.9 0.452 30 neg
## 128 1 118 58 36 94 33.3 0.261 23 neg
## 129 1 117 88 24 145 34.5 0.403 40 pos
## 130 0 105 84 0 0 27.9 0.741 62 pos
## 131 4 173 70 14 168 29.7 0.361 33 pos
## 132 9 122 56 0 0 33.3 1.114 33 pos
## 133 3 170 64 37 225 34.5 0.356 30 pos
## 134 8 84 74 31 0 38.3 0.457 39 neg
## 135 2 96 68 13 49 21.1 0.647 26 neg
## 136 2 125 60 20 140 33.8 0.088 31 neg
## 137 0 100 70 26 50 30.8 0.597 21 neg
## 138 0 93 60 25 92 28.7 0.532 22 neg
## 139 0 129 80 0 0 31.2 0.703 29 neg
## 140 5 105 72 29 325 36.9 0.159 28 neg
## 141 3 128 78 0 0 21.1 0.268 55 neg
## 142 5 106 82 30 0 39.5 0.286 38 neg
## 143 2 108 52 26 63 32.5 0.318 22 neg
## 144 10 108 66 0 0 32.4 0.272 42 pos
## 145 4 154 62 31 284 32.8 0.237 23 neg
## 146 0 102 75 23 0 0.0 0.572 21 neg
## 147 9 57 80 37 0 32.8 0.096 41 neg
## 148 2 106 64 35 119 30.5 1.400 34 neg
## 149 5 147 78 0 0 33.7 0.218 65 neg
## 150 2 90 70 17 0 27.3 0.085 22 neg
## 151 1 136 74 50 204 37.4 0.399 24 neg
## 152 4 114 65 0 0 21.9 0.432 37 neg
## 153 9 156 86 28 155 34.3 1.189 42 pos
## 154 1 153 82 42 485 40.6 0.687 23 neg
## 155 8 188 78 0 0 47.9 0.137 43 pos
## 156 7 152 88 44 0 50.0 0.337 36 pos
## 157 2 99 52 15 94 24.6 0.637 21 neg
## 158 1 109 56 21 135 25.2 0.833 23 neg
## 159 2 88 74 19 53 29.0 0.229 22 neg
## 160 17 163 72 41 114 40.9 0.817 47 pos
## 161 4 151 90 38 0 29.7 0.294 36 neg
## 162 7 102 74 40 105 37.2 0.204 45 neg
## 163 0 114 80 34 285 44.2 0.167 27 neg
## 164 2 100 64 23 0 29.7 0.368 21 neg
## 165 0 131 88 0 0 31.6 0.743 32 pos
## 166 6 104 74 18 156 29.9 0.722 41 pos
## 167 3 148 66 25 0 32.5 0.256 22 neg
## 168 4 120 68 0 0 29.6 0.709 34 neg
## 169 4 110 66 0 0 31.9 0.471 29 neg
## 170 3 111 90 12 78 28.4 0.495 29 neg
## 171 6 102 82 0 0 30.8 0.180 36 pos
## 172 6 134 70 23 130 35.4 0.542 29 pos
## 173 2 87 0 23 0 28.9 0.773 25 neg
## 174 1 79 60 42 48 43.5 0.678 23 neg
## 175 2 75 64 24 55 29.7 0.370 33 neg
## 176 8 179 72 42 130 32.7 0.719 36 pos
## 177 6 85 78 0 0 31.2 0.382 42 neg
## 178 0 129 110 46 130 67.1 0.319 26 pos
## 179 5 143 78 0 0 45.0 0.190 47 neg
## 180 5 130 82 0 0 39.1 0.956 37 pos
## 181 6 87 80 0 0 23.2 0.084 32 neg
## 182 0 119 64 18 92 34.9 0.725 23 neg
## 183 1 0 74 20 23 27.7 0.299 21 neg
## 184 5 73 60 0 0 26.8 0.268 27 neg
## 185 4 141 74 0 0 27.6 0.244 40 neg
## 186 7 194 68 28 0 35.9 0.745 41 pos
## 187 8 181 68 36 495 30.1 0.615 60 pos
## 188 1 128 98 41 58 32.0 1.321 33 pos
## 189 8 109 76 39 114 27.9 0.640 31 pos
## 190 5 139 80 35 160 31.6 0.361 25 pos
## 191 3 111 62 0 0 22.6 0.142 21 neg
## 192 9 123 70 44 94 33.1 0.374 40 neg
## 193 7 159 66 0 0 30.4 0.383 36 pos
## 194 11 135 0 0 0 52.3 0.578 40 pos
## 195 8 85 55 20 0 24.4 0.136 42 neg
## 196 5 158 84 41 210 39.4 0.395 29 pos
## 197 1 105 58 0 0 24.3 0.187 21 neg
## 198 3 107 62 13 48 22.9 0.678 23 pos
## 199 4 109 64 44 99 34.8 0.905 26 pos
## 200 4 148 60 27 318 30.9 0.150 29 pos
## 201 0 113 80 16 0 31.0 0.874 21 neg
## 202 1 138 82 0 0 40.1 0.236 28 neg
## 203 0 108 68 20 0 27.3 0.787 32 neg
## 204 2 99 70 16 44 20.4 0.235 27 neg
## 205 6 103 72 32 190 37.7 0.324 55 neg
## 206 5 111 72 28 0 23.9 0.407 27 neg
## 207 8 196 76 29 280 37.5 0.605 57 pos
## 208 5 162 104 0 0 37.7 0.151 52 pos
## 209 1 96 64 27 87 33.2 0.289 21 neg
## 210 7 184 84 33 0 35.5 0.355 41 pos
## 211 2 81 60 22 0 27.7 0.290 25 neg
## 212 0 147 85 54 0 42.8 0.375 24 neg
## 213 7 179 95 31 0 34.2 0.164 60 neg
## 214 0 140 65 26 130 42.6 0.431 24 pos
## 215 9 112 82 32 175 34.2 0.260 36 pos
## 216 12 151 70 40 271 41.8 0.742 38 pos
## 217 5 109 62 41 129 35.8 0.514 25 pos
## 218 6 125 68 30 120 30.0 0.464 32 neg
## 219 5 85 74 22 0 29.0 1.224 32 pos
## 220 5 112 66 0 0 37.8 0.261 41 pos
## 221 0 177 60 29 478 34.6 1.072 21 pos
## 222 2 158 90 0 0 31.6 0.805 66 pos
## 223 7 119 0 0 0 25.2 0.209 37 neg
## 224 7 142 60 33 190 28.8 0.687 61 neg
## 225 1 100 66 15 56 23.6 0.666 26 neg
## 226 1 87 78 27 32 34.6 0.101 22 neg
## 227 0 101 76 0 0 35.7 0.198 26 neg
## 228 3 162 52 38 0 37.2 0.652 24 pos
## 229 4 197 70 39 744 36.7 2.329 31 neg
## 230 0 117 80 31 53 45.2 0.089 24 neg
## 231 4 142 86 0 0 44.0 0.645 22 pos
## 232 6 134 80 37 370 46.2 0.238 46 pos
## 233 1 79 80 25 37 25.4 0.583 22 neg
## 234 4 122 68 0 0 35.0 0.394 29 neg
## 235 3 74 68 28 45 29.7 0.293 23 neg
## 236 4 171 72 0 0 43.6 0.479 26 pos
## 237 7 181 84 21 192 35.9 0.586 51 pos
## 238 0 179 90 27 0 44.1 0.686 23 pos
## 239 9 164 84 21 0 30.8 0.831 32 pos
## 240 0 104 76 0 0 18.4 0.582 27 neg
## 241 1 91 64 24 0 29.2 0.192 21 neg
## 242 4 91 70 32 88 33.1 0.446 22 neg
## 243 3 139 54 0 0 25.6 0.402 22 pos
## 244 6 119 50 22 176 27.1 1.318 33 pos
## 245 2 146 76 35 194 38.2 0.329 29 neg
## 246 9 184 85 15 0 30.0 1.213 49 pos
## 247 10 122 68 0 0 31.2 0.258 41 neg
## 248 0 165 90 33 680 52.3 0.427 23 neg
## 249 9 124 70 33 402 35.4 0.282 34 neg
## 250 1 111 86 19 0 30.1 0.143 23 neg
## 251 9 106 52 0 0 31.2 0.380 42 neg
## 252 2 129 84 0 0 28.0 0.284 27 neg
## 253 2 90 80 14 55 24.4 0.249 24 neg
## 254 0 86 68 32 0 35.8 0.238 25 neg
## 255 12 92 62 7 258 27.6 0.926 44 pos
## 256 1 113 64 35 0 33.6 0.543 21 pos
## 257 3 111 56 39 0 30.1 0.557 30 neg
## 258 2 114 68 22 0 28.7 0.092 25 neg
## 259 1 193 50 16 375 25.9 0.655 24 neg
## 260 11 155 76 28 150 33.3 1.353 51 pos
## 261 3 191 68 15 130 30.9 0.299 34 neg
## 262 3 141 0 0 0 30.0 0.761 27 pos
## 263 4 95 70 32 0 32.1 0.612 24 neg
## 264 3 142 80 15 0 32.4 0.200 63 neg
## 265 4 123 62 0 0 32.0 0.226 35 pos
## 266 5 96 74 18 67 33.6 0.997 43 neg
## 267 0 138 0 0 0 36.3 0.933 25 pos
## 268 2 128 64 42 0 40.0 1.101 24 neg
## 269 0 102 52 0 0 25.1 0.078 21 neg
## 270 2 146 0 0 0 27.5 0.240 28 pos
## 271 10 101 86 37 0 45.6 1.136 38 pos
## 272 2 108 62 32 56 25.2 0.128 21 neg
## 273 3 122 78 0 0 23.0 0.254 40 neg
## 274 1 71 78 50 45 33.2 0.422 21 neg
## 275 13 106 70 0 0 34.2 0.251 52 neg
## 276 2 100 70 52 57 40.5 0.677 25 neg
## 277 7 106 60 24 0 26.5 0.296 29 pos
## 278 0 104 64 23 116 27.8 0.454 23 neg
## 279 5 114 74 0 0 24.9 0.744 57 neg
## 280 2 108 62 10 278 25.3 0.881 22 neg
## 281 0 146 70 0 0 37.9 0.334 28 pos
## 282 10 129 76 28 122 35.9 0.280 39 neg
## 283 7 133 88 15 155 32.4 0.262 37 neg
## 284 7 161 86 0 0 30.4 0.165 47 pos
## 285 2 108 80 0 0 27.0 0.259 52 pos
## 286 7 136 74 26 135 26.0 0.647 51 neg
## 287 5 155 84 44 545 38.7 0.619 34 neg
## 288 1 119 86 39 220 45.6 0.808 29 pos
## 289 4 96 56 17 49 20.8 0.340 26 neg
## 290 5 108 72 43 75 36.1 0.263 33 neg
## 291 0 78 88 29 40 36.9 0.434 21 neg
## 292 0 107 62 30 74 36.6 0.757 25 pos
## 293 2 128 78 37 182 43.3 1.224 31 pos
## 294 1 128 48 45 194 40.5 0.613 24 pos
## 295 0 161 50 0 0 21.9 0.254 65 neg
## 296 6 151 62 31 120 35.5 0.692 28 neg
## 297 2 146 70 38 360 28.0 0.337 29 pos
## 298 0 126 84 29 215 30.7 0.520 24 neg
## 299 14 100 78 25 184 36.6 0.412 46 pos
## 300 8 112 72 0 0 23.6 0.840 58 neg
## 301 0 167 0 0 0 32.3 0.839 30 pos
## 302 2 144 58 33 135 31.6 0.422 25 pos
## 303 5 77 82 41 42 35.8 0.156 35 neg
## 304 5 115 98 0 0 52.9 0.209 28 pos
## 305 3 150 76 0 0 21.0 0.207 37 neg
## 306 2 120 76 37 105 39.7 0.215 29 neg
## 307 10 161 68 23 132 25.5 0.326 47 pos
## 308 0 137 68 14 148 24.8 0.143 21 neg
## 309 0 128 68 19 180 30.5 1.391 25 pos
## 310 2 124 68 28 205 32.9 0.875 30 pos
## 311 6 80 66 30 0 26.2 0.313 41 neg
## 312 0 106 70 37 148 39.4 0.605 22 neg
## 313 2 155 74 17 96 26.6 0.433 27 pos
## 314 3 113 50 10 85 29.5 0.626 25 neg
## 315 7 109 80 31 0 35.9 1.127 43 pos
## 316 2 112 68 22 94 34.1 0.315 26 neg
## 317 3 99 80 11 64 19.3 0.284 30 neg
## 318 3 182 74 0 0 30.5 0.345 29 pos
## 319 3 115 66 39 140 38.1 0.150 28 neg
## 320 6 194 78 0 0 23.5 0.129 59 pos
## 321 4 129 60 12 231 27.5 0.527 31 neg
## 322 3 112 74 30 0 31.6 0.197 25 pos
## 323 0 124 70 20 0 27.4 0.254 36 pos
## 324 13 152 90 33 29 26.8 0.731 43 pos
## 325 2 112 75 32 0 35.7 0.148 21 neg
## 326 1 157 72 21 168 25.6 0.123 24 neg
## 327 1 122 64 32 156 35.1 0.692 30 pos
## 328 10 179 70 0 0 35.1 0.200 37 neg
## 329 2 102 86 36 120 45.5 0.127 23 pos
## 330 6 105 70 32 68 30.8 0.122 37 neg
## 331 8 118 72 19 0 23.1 1.476 46 neg
## 332 2 87 58 16 52 32.7 0.166 25 neg
## 333 1 180 0 0 0 43.3 0.282 41 pos
## 334 12 106 80 0 0 23.6 0.137 44 neg
## 335 1 95 60 18 58 23.9 0.260 22 neg
## 336 0 165 76 43 255 47.9 0.259 26 neg
## 337 0 117 0 0 0 33.8 0.932 44 neg
## 338 5 115 76 0 0 31.2 0.343 44 pos
## 339 9 152 78 34 171 34.2 0.893 33 pos
## 340 7 178 84 0 0 39.9 0.331 41 pos
## 341 1 130 70 13 105 25.9 0.472 22 neg
## 342 1 95 74 21 73 25.9 0.673 36 neg
## 343 1 0 68 35 0 32.0 0.389 22 neg
## 344 5 122 86 0 0 34.7 0.290 33 neg
## 345 8 95 72 0 0 36.8 0.485 57 neg
## 346 8 126 88 36 108 38.5 0.349 49 neg
## 347 1 139 46 19 83 28.7 0.654 22 neg
## 348 3 116 0 0 0 23.5 0.187 23 neg
## 349 3 99 62 19 74 21.8 0.279 26 neg
## 350 5 0 80 32 0 41.0 0.346 37 pos
## 351 4 92 80 0 0 42.2 0.237 29 neg
## 352 4 137 84 0 0 31.2 0.252 30 neg
## 353 3 61 82 28 0 34.4 0.243 46 neg
## 354 1 90 62 12 43 27.2 0.580 24 neg
## 355 3 90 78 0 0 42.7 0.559 21 neg
## 356 9 165 88 0 0 30.4 0.302 49 pos
## 357 1 125 50 40 167 33.3 0.962 28 pos
## 358 13 129 0 30 0 39.9 0.569 44 pos
## 359 12 88 74 40 54 35.3 0.378 48 neg
## 360 1 196 76 36 249 36.5 0.875 29 pos
## 361 5 189 64 33 325 31.2 0.583 29 pos
## 362 5 158 70 0 0 29.8 0.207 63 neg
## 363 5 103 108 37 0 39.2 0.305 65 neg
## 364 4 146 78 0 0 38.5 0.520 67 pos
## 365 4 147 74 25 293 34.9 0.385 30 neg
## 366 5 99 54 28 83 34.0 0.499 30 neg
## 367 6 124 72 0 0 27.6 0.368 29 pos
## 368 0 101 64 17 0 21.0 0.252 21 neg
## 369 3 81 86 16 66 27.5 0.306 22 neg
## 370 1 133 102 28 140 32.8 0.234 45 pos
## 371 3 173 82 48 465 38.4 2.137 25 pos
## 372 0 118 64 23 89 0.0 1.731 21 neg
## 373 0 84 64 22 66 35.8 0.545 21 neg
## 374 2 105 58 40 94 34.9 0.225 25 neg
## 375 2 122 52 43 158 36.2 0.816 28 neg
## 376 12 140 82 43 325 39.2 0.528 58 pos
## 377 0 98 82 15 84 25.2 0.299 22 neg
## 378 1 87 60 37 75 37.2 0.509 22 neg
## 379 4 156 75 0 0 48.3 0.238 32 pos
## 380 0 93 100 39 72 43.4 1.021 35 neg
## 381 1 107 72 30 82 30.8 0.821 24 neg
## 382 0 105 68 22 0 20.0 0.236 22 neg
## 383 1 109 60 8 182 25.4 0.947 21 neg
## 384 1 90 62 18 59 25.1 1.268 25 neg
## 385 1 125 70 24 110 24.3 0.221 25 neg
## 386 1 119 54 13 50 22.3 0.205 24 neg
## 387 5 116 74 29 0 32.3 0.660 35 pos
## 388 8 105 100 36 0 43.3 0.239 45 pos
## 389 5 144 82 26 285 32.0 0.452 58 pos
## 390 3 100 68 23 81 31.6 0.949 28 neg
## 391 1 100 66 29 196 32.0 0.444 42 neg
## 392 5 166 76 0 0 45.7 0.340 27 pos
## 393 1 131 64 14 415 23.7 0.389 21 neg
## 394 4 116 72 12 87 22.1 0.463 37 neg
## 395 4 158 78 0 0 32.9 0.803 31 pos
## 396 2 127 58 24 275 27.7 1.600 25 neg
## 397 3 96 56 34 115 24.7 0.944 39 neg
## 398 0 131 66 40 0 34.3 0.196 22 pos
## 399 3 82 70 0 0 21.1 0.389 25 neg
## 400 3 193 70 31 0 34.9 0.241 25 pos
## 401 4 95 64 0 0 32.0 0.161 31 pos
## 402 6 137 61 0 0 24.2 0.151 55 neg
## 403 5 136 84 41 88 35.0 0.286 35 pos
## 404 9 72 78 25 0 31.6 0.280 38 neg
## 405 5 168 64 0 0 32.9 0.135 41 pos
## 406 2 123 48 32 165 42.1 0.520 26 neg
## 407 4 115 72 0 0 28.9 0.376 46 pos
## 408 0 101 62 0 0 21.9 0.336 25 neg
## 409 8 197 74 0 0 25.9 1.191 39 pos
## 410 1 172 68 49 579 42.4 0.702 28 pos
## 411 6 102 90 39 0 35.7 0.674 28 neg
## 412 1 112 72 30 176 34.4 0.528 25 neg
## 413 1 143 84 23 310 42.4 1.076 22 neg
## 414 1 143 74 22 61 26.2 0.256 21 neg
## 415 0 138 60 35 167 34.6 0.534 21 pos
## 416 3 173 84 33 474 35.7 0.258 22 pos
## 417 1 97 68 21 0 27.2 1.095 22 neg
## 418 4 144 82 32 0 38.5 0.554 37 pos
## 419 1 83 68 0 0 18.2 0.624 27 neg
## 420 3 129 64 29 115 26.4 0.219 28 pos
## 421 1 119 88 41 170 45.3 0.507 26 neg
## 422 2 94 68 18 76 26.0 0.561 21 neg
## 423 0 102 64 46 78 40.6 0.496 21 neg
## 424 2 115 64 22 0 30.8 0.421 21 neg
## 425 8 151 78 32 210 42.9 0.516 36 pos
## 426 4 184 78 39 277 37.0 0.264 31 pos
## 427 0 94 0 0 0 0.0 0.256 25 neg
## 428 1 181 64 30 180 34.1 0.328 38 pos
## 429 0 135 94 46 145 40.6 0.284 26 neg
## 430 1 95 82 25 180 35.0 0.233 43 pos
## 431 2 99 0 0 0 22.2 0.108 23 neg
## 432 3 89 74 16 85 30.4 0.551 38 neg
## 433 1 80 74 11 60 30.0 0.527 22 neg
## 434 2 139 75 0 0 25.6 0.167 29 neg
## 435 1 90 68 8 0 24.5 1.138 36 neg
## 436 0 141 0 0 0 42.4 0.205 29 pos
## 437 12 140 85 33 0 37.4 0.244 41 neg
## 438 5 147 75 0 0 29.9 0.434 28 neg
## 439 1 97 70 15 0 18.2 0.147 21 neg
## 440 6 107 88 0 0 36.8 0.727 31 neg
## 441 0 189 104 25 0 34.3 0.435 41 pos
## 442 2 83 66 23 50 32.2 0.497 22 neg
## 443 4 117 64 27 120 33.2 0.230 24 neg
## 444 8 108 70 0 0 30.5 0.955 33 pos
## 445 4 117 62 12 0 29.7 0.380 30 pos
## 446 0 180 78 63 14 59.4 2.420 25 pos
## 447 1 100 72 12 70 25.3 0.658 28 neg
## 448 0 95 80 45 92 36.5 0.330 26 neg
## 449 0 104 64 37 64 33.6 0.510 22 pos
## 450 0 120 74 18 63 30.5 0.285 26 neg
## 451 1 82 64 13 95 21.2 0.415 23 neg
## 452 2 134 70 0 0 28.9 0.542 23 pos
## 453 0 91 68 32 210 39.9 0.381 25 neg
## 454 2 119 0 0 0 19.6 0.832 72 neg
## 455 2 100 54 28 105 37.8 0.498 24 neg
## 456 14 175 62 30 0 33.6 0.212 38 pos
## 457 1 135 54 0 0 26.7 0.687 62 neg
## 458 5 86 68 28 71 30.2 0.364 24 neg
## 459 10 148 84 48 237 37.6 1.001 51 pos
## 460 9 134 74 33 60 25.9 0.460 81 neg
## 461 9 120 72 22 56 20.8 0.733 48 neg
## 462 1 71 62 0 0 21.8 0.416 26 neg
## 463 8 74 70 40 49 35.3 0.705 39 neg
## 464 5 88 78 30 0 27.6 0.258 37 neg
## 465 10 115 98 0 0 24.0 1.022 34 neg
## 466 0 124 56 13 105 21.8 0.452 21 neg
## 467 0 74 52 10 36 27.8 0.269 22 neg
## 468 0 97 64 36 100 36.8 0.600 25 neg
## 469 8 120 0 0 0 30.0 0.183 38 pos
## 470 6 154 78 41 140 46.1 0.571 27 neg
## 471 1 144 82 40 0 41.3 0.607 28 neg
## 472 0 137 70 38 0 33.2 0.170 22 neg
## 473 0 119 66 27 0 38.8 0.259 22 neg
## 474 7 136 90 0 0 29.9 0.210 50 neg
## 475 4 114 64 0 0 28.9 0.126 24 neg
## 476 0 137 84 27 0 27.3 0.231 59 neg
## 477 2 105 80 45 191 33.7 0.711 29 pos
## 478 7 114 76 17 110 23.8 0.466 31 neg
## 479 8 126 74 38 75 25.9 0.162 39 neg
## 480 4 132 86 31 0 28.0 0.419 63 neg
## 481 3 158 70 30 328 35.5 0.344 35 pos
## 482 0 123 88 37 0 35.2 0.197 29 neg
## 483 4 85 58 22 49 27.8 0.306 28 neg
## 484 0 84 82 31 125 38.2 0.233 23 neg
## 485 0 145 0 0 0 44.2 0.630 31 pos
## 486 0 135 68 42 250 42.3 0.365 24 pos
## 487 1 139 62 41 480 40.7 0.536 21 neg
## 488 0 173 78 32 265 46.5 1.159 58 neg
## 489 4 99 72 17 0 25.6 0.294 28 neg
## 490 8 194 80 0 0 26.1 0.551 67 neg
## 491 2 83 65 28 66 36.8 0.629 24 neg
## 492 2 89 90 30 0 33.5 0.292 42 neg
## 493 4 99 68 38 0 32.8 0.145 33 neg
## 494 4 125 70 18 122 28.9 1.144 45 pos
## 495 3 80 0 0 0 0.0 0.174 22 neg
## 496 6 166 74 0 0 26.6 0.304 66 neg
## 497 5 110 68 0 0 26.0 0.292 30 neg
## 498 2 81 72 15 76 30.1 0.547 25 neg
## 499 7 195 70 33 145 25.1 0.163 55 pos
## 500 6 154 74 32 193 29.3 0.839 39 neg
## 501 2 117 90 19 71 25.2 0.313 21 neg
## 502 3 84 72 32 0 37.2 0.267 28 neg
## 503 6 0 68 41 0 39.0 0.727 41 pos
## 504 7 94 64 25 79 33.3 0.738 41 neg
## 505 3 96 78 39 0 37.3 0.238 40 neg
## 506 10 75 82 0 0 33.3 0.263 38 neg
## 507 0 180 90 26 90 36.5 0.314 35 pos
## 508 1 130 60 23 170 28.6 0.692 21 neg
## 509 2 84 50 23 76 30.4 0.968 21 neg
## 510 8 120 78 0 0 25.0 0.409 64 neg
## 511 12 84 72 31 0 29.7 0.297 46 pos
## 512 0 139 62 17 210 22.1 0.207 21 neg
## 513 9 91 68 0 0 24.2 0.200 58 neg
## 514 2 91 62 0 0 27.3 0.525 22 neg
## 515 3 99 54 19 86 25.6 0.154 24 neg
## 516 3 163 70 18 105 31.6 0.268 28 pos
## 517 9 145 88 34 165 30.3 0.771 53 pos
## 518 7 125 86 0 0 37.6 0.304 51 neg
## 519 13 76 60 0 0 32.8 0.180 41 neg
## 520 6 129 90 7 326 19.6 0.582 60 neg
## 521 2 68 70 32 66 25.0 0.187 25 neg
## 522 3 124 80 33 130 33.2 0.305 26 neg
## 523 6 114 0 0 0 0.0 0.189 26 neg
## 524 9 130 70 0 0 34.2 0.652 45 pos
## 525 3 125 58 0 0 31.6 0.151 24 neg
## 526 3 87 60 18 0 21.8 0.444 21 neg
## 527 1 97 64 19 82 18.2 0.299 21 neg
## 528 3 116 74 15 105 26.3 0.107 24 neg
## 529 0 117 66 31 188 30.8 0.493 22 neg
## 530 0 111 65 0 0 24.6 0.660 31 neg
## 531 2 122 60 18 106 29.8 0.717 22 neg
## 532 0 107 76 0 0 45.3 0.686 24 neg
## 533 1 86 66 52 65 41.3 0.917 29 neg
## 534 6 91 0 0 0 29.8 0.501 31 neg
## 535 1 77 56 30 56 33.3 1.251 24 neg
## 536 4 132 0 0 0 32.9 0.302 23 pos
## 537 0 105 90 0 0 29.6 0.197 46 neg
## 538 0 57 60 0 0 21.7 0.735 67 neg
## 539 0 127 80 37 210 36.3 0.804 23 neg
## 540 3 129 92 49 155 36.4 0.968 32 pos
## 541 8 100 74 40 215 39.4 0.661 43 pos
## 542 3 128 72 25 190 32.4 0.549 27 pos
## 543 10 90 85 32 0 34.9 0.825 56 pos
## 544 4 84 90 23 56 39.5 0.159 25 neg
## 545 1 88 78 29 76 32.0 0.365 29 neg
## 546 8 186 90 35 225 34.5 0.423 37 pos
## 547 5 187 76 27 207 43.6 1.034 53 pos
## 548 4 131 68 21 166 33.1 0.160 28 neg
## 549 1 164 82 43 67 32.8 0.341 50 neg
## 550 4 189 110 31 0 28.5 0.680 37 neg
## 551 1 116 70 28 0 27.4 0.204 21 neg
## 552 3 84 68 30 106 31.9 0.591 25 neg
## 553 6 114 88 0 0 27.8 0.247 66 neg
## 554 1 88 62 24 44 29.9 0.422 23 neg
## 555 1 84 64 23 115 36.9 0.471 28 neg
## 556 7 124 70 33 215 25.5 0.161 37 neg
## 557 1 97 70 40 0 38.1 0.218 30 neg
## 558 8 110 76 0 0 27.8 0.237 58 neg
## 559 11 103 68 40 0 46.2 0.126 42 neg
## 560 11 85 74 0 0 30.1 0.300 35 neg
## 561 6 125 76 0 0 33.8 0.121 54 pos
## 562 0 198 66 32 274 41.3 0.502 28 pos
## 563 1 87 68 34 77 37.6 0.401 24 neg
## 564 6 99 60 19 54 26.9 0.497 32 neg
## 565 0 91 80 0 0 32.4 0.601 27 neg
## 566 2 95 54 14 88 26.1 0.748 22 neg
## 567 1 99 72 30 18 38.6 0.412 21 neg
## 568 6 92 62 32 126 32.0 0.085 46 neg
## 569 4 154 72 29 126 31.3 0.338 37 neg
## 570 0 121 66 30 165 34.3 0.203 33 pos
## 571 3 78 70 0 0 32.5 0.270 39 neg
## 572 2 130 96 0 0 22.6 0.268 21 neg
## 573 3 111 58 31 44 29.5 0.430 22 neg
## 574 2 98 60 17 120 34.7 0.198 22 neg
## 575 1 143 86 30 330 30.1 0.892 23 neg
## 576 1 119 44 47 63 35.5 0.280 25 neg
## 577 6 108 44 20 130 24.0 0.813 35 neg
## 578 2 118 80 0 0 42.9 0.693 21 pos
## 579 10 133 68 0 0 27.0 0.245 36 neg
## 580 2 197 70 99 0 34.7 0.575 62 pos
## 581 0 151 90 46 0 42.1 0.371 21 pos
## 582 6 109 60 27 0 25.0 0.206 27 neg
## 583 12 121 78 17 0 26.5 0.259 62 neg
## 584 8 100 76 0 0 38.7 0.190 42 neg
## 585 8 124 76 24 600 28.7 0.687 52 pos
## 586 1 93 56 11 0 22.5 0.417 22 neg
## 587 8 143 66 0 0 34.9 0.129 41 pos
## 588 6 103 66 0 0 24.3 0.249 29 neg
## 589 3 176 86 27 156 33.3 1.154 52 pos
## 590 0 73 0 0 0 21.1 0.342 25 neg
## 591 11 111 84 40 0 46.8 0.925 45 pos
## 592 2 112 78 50 140 39.4 0.175 24 neg
## 593 3 132 80 0 0 34.4 0.402 44 pos
## 594 2 82 52 22 115 28.5 1.699 25 neg
## 595 6 123 72 45 230 33.6 0.733 34 neg
## 596 0 188 82 14 185 32.0 0.682 22 pos
## 597 0 67 76 0 0 45.3 0.194 46 neg
## 598 1 89 24 19 25 27.8 0.559 21 neg
## 599 1 173 74 0 0 36.8 0.088 38 pos
## 600 1 109 38 18 120 23.1 0.407 26 neg
## 601 1 108 88 19 0 27.1 0.400 24 neg
## 602 6 96 0 0 0 23.7 0.190 28 neg
## 603 1 124 74 36 0 27.8 0.100 30 neg
## 604 7 150 78 29 126 35.2 0.692 54 pos
## 605 4 183 0 0 0 28.4 0.212 36 pos
## 606 1 124 60 32 0 35.8 0.514 21 neg
## 607 1 181 78 42 293 40.0 1.258 22 pos
## 608 1 92 62 25 41 19.5 0.482 25 neg
## 609 0 152 82 39 272 41.5 0.270 27 neg
## 610 1 111 62 13 182 24.0 0.138 23 neg
## 611 3 106 54 21 158 30.9 0.292 24 neg
## 612 3 174 58 22 194 32.9 0.593 36 pos
## 613 7 168 88 42 321 38.2 0.787 40 pos
## 614 6 105 80 28 0 32.5 0.878 26 neg
## 615 11 138 74 26 144 36.1 0.557 50 pos
## 616 3 106 72 0 0 25.8 0.207 27 neg
## 617 6 117 96 0 0 28.7 0.157 30 neg
## 618 2 68 62 13 15 20.1 0.257 23 neg
## 619 9 112 82 24 0 28.2 1.282 50 pos
## 620 0 119 0 0 0 32.4 0.141 24 pos
## 621 2 112 86 42 160 38.4 0.246 28 neg
## 622 2 92 76 20 0 24.2 1.698 28 neg
## 623 6 183 94 0 0 40.8 1.461 45 neg
## 624 0 94 70 27 115 43.5 0.347 21 neg
## 625 2 108 64 0 0 30.8 0.158 21 neg
## 626 4 90 88 47 54 37.7 0.362 29 neg
## 627 0 125 68 0 0 24.7 0.206 21 neg
## 628 0 132 78 0 0 32.4 0.393 21 neg
## 629 5 128 80 0 0 34.6 0.144 45 neg
## 630 4 94 65 22 0 24.7 0.148 21 neg
## 631 7 114 64 0 0 27.4 0.732 34 pos
## 632 0 102 78 40 90 34.5 0.238 24 neg
## 633 2 111 60 0 0 26.2 0.343 23 neg
## 634 1 128 82 17 183 27.5 0.115 22 neg
## 635 10 92 62 0 0 25.9 0.167 31 neg
## 636 13 104 72 0 0 31.2 0.465 38 pos
## 637 5 104 74 0 0 28.8 0.153 48 neg
## 638 2 94 76 18 66 31.6 0.649 23 neg
## 639 7 97 76 32 91 40.9 0.871 32 pos
## 640 1 100 74 12 46 19.5 0.149 28 neg
## 641 0 102 86 17 105 29.3 0.695 27 neg
## 642 4 128 70 0 0 34.3 0.303 24 neg
## 643 6 147 80 0 0 29.5 0.178 50 pos
## 644 4 90 0 0 0 28.0 0.610 31 neg
## 645 3 103 72 30 152 27.6 0.730 27 neg
## 646 2 157 74 35 440 39.4 0.134 30 neg
## 647 1 167 74 17 144 23.4 0.447 33 pos
## 648 0 179 50 36 159 37.8 0.455 22 pos
## 649 11 136 84 35 130 28.3 0.260 42 pos
## 650 0 107 60 25 0 26.4 0.133 23 neg
## 651 1 91 54 25 100 25.2 0.234 23 neg
## 652 1 117 60 23 106 33.8 0.466 27 neg
## 653 5 123 74 40 77 34.1 0.269 28 neg
## 654 2 120 54 0 0 26.8 0.455 27 neg
## 655 1 106 70 28 135 34.2 0.142 22 neg
## 656 2 155 52 27 540 38.7 0.240 25 pos
## 657 2 101 58 35 90 21.8 0.155 22 neg
## 658 1 120 80 48 200 38.9 1.162 41 neg
## 659 11 127 106 0 0 39.0 0.190 51 neg
## 660 3 80 82 31 70 34.2 1.292 27 pos
## 661 10 162 84 0 0 27.7 0.182 54 neg
## 662 1 199 76 43 0 42.9 1.394 22 pos
## 663 8 167 106 46 231 37.6 0.165 43 pos
## 664 9 145 80 46 130 37.9 0.637 40 pos
## 665 6 115 60 39 0 33.7 0.245 40 pos
## 666 1 112 80 45 132 34.8 0.217 24 neg
## 667 4 145 82 18 0 32.5 0.235 70 pos
## 668 10 111 70 27 0 27.5 0.141 40 pos
## 669 6 98 58 33 190 34.0 0.430 43 neg
## 670 9 154 78 30 100 30.9 0.164 45 neg
## 671 6 165 68 26 168 33.6 0.631 49 neg
## 672 1 99 58 10 0 25.4 0.551 21 neg
## 673 10 68 106 23 49 35.5 0.285 47 neg
## 674 3 123 100 35 240 57.3 0.880 22 neg
## 675 8 91 82 0 0 35.6 0.587 68 neg
## 676 6 195 70 0 0 30.9 0.328 31 pos
## 677 9 156 86 0 0 24.8 0.230 53 pos
## 678 0 93 60 0 0 35.3 0.263 25 neg
## 679 3 121 52 0 0 36.0 0.127 25 pos
## 680 2 101 58 17 265 24.2 0.614 23 neg
## 681 2 56 56 28 45 24.2 0.332 22 neg
## 682 0 162 76 36 0 49.6 0.364 26 pos
## 683 0 95 64 39 105 44.6 0.366 22 neg
## 684 4 125 80 0 0 32.3 0.536 27 pos
## 685 5 136 82 0 0 0.0 0.640 69 neg
## 686 2 129 74 26 205 33.2 0.591 25 neg
## 687 3 130 64 0 0 23.1 0.314 22 neg
## 688 1 107 50 19 0 28.3 0.181 29 neg
## 689 1 140 74 26 180 24.1 0.828 23 neg
## 690 1 144 82 46 180 46.1 0.335 46 pos
## 691 8 107 80 0 0 24.6 0.856 34 neg
## 692 13 158 114 0 0 42.3 0.257 44 pos
## 693 2 121 70 32 95 39.1 0.886 23 neg
## 694 7 129 68 49 125 38.5 0.439 43 pos
## 695 2 90 60 0 0 23.5 0.191 25 neg
## 696 7 142 90 24 480 30.4 0.128 43 pos
## 697 3 169 74 19 125 29.9 0.268 31 pos
## 698 0 99 0 0 0 25.0 0.253 22 neg
## 699 4 127 88 11 155 34.5 0.598 28 neg
## 700 4 118 70 0 0 44.5 0.904 26 neg
## 701 2 122 76 27 200 35.9 0.483 26 neg
## 702 6 125 78 31 0 27.6 0.565 49 pos
## 703 1 168 88 29 0 35.0 0.905 52 pos
## 704 2 129 0 0 0 38.5 0.304 41 neg
## 705 4 110 76 20 100 28.4 0.118 27 neg
## 706 6 80 80 36 0 39.8 0.177 28 neg
## 707 10 115 0 0 0 0.0 0.261 30 pos
## 708 2 127 46 21 335 34.4 0.176 22 neg
## 709 9 164 78 0 0 32.8 0.148 45 pos
## 710 2 93 64 32 160 38.0 0.674 23 pos
## 711 3 158 64 13 387 31.2 0.295 24 neg
## 712 5 126 78 27 22 29.6 0.439 40 neg
## 713 10 129 62 36 0 41.2 0.441 38 pos
## 714 0 134 58 20 291 26.4 0.352 21 neg
## 715 3 102 74 0 0 29.5 0.121 32 neg
## 716 7 187 50 33 392 33.9 0.826 34 pos
## 717 3 173 78 39 185 33.8 0.970 31 pos
## 718 10 94 72 18 0 23.1 0.595 56 neg
## 719 1 108 60 46 178 35.5 0.415 24 neg
## 720 5 97 76 27 0 35.6 0.378 52 pos
## 721 4 83 86 19 0 29.3 0.317 34 neg
## 722 1 114 66 36 200 38.1 0.289 21 neg
## 723 1 149 68 29 127 29.3 0.349 42 pos
## 724 5 117 86 30 105 39.1 0.251 42 neg
## 725 1 111 94 0 0 32.8 0.265 45 neg
## 726 4 112 78 40 0 39.4 0.236 38 neg
## 727 1 116 78 29 180 36.1 0.496 25 neg
## 728 0 141 84 26 0 32.4 0.433 22 neg
## 729 2 175 88 0 0 22.9 0.326 22 neg
## 730 2 92 52 0 0 30.1 0.141 22 neg
## 731 3 130 78 23 79 28.4 0.323 34 pos
## 732 8 120 86 0 0 28.4 0.259 22 pos
## 733 2 174 88 37 120 44.5 0.646 24 pos
## 734 2 106 56 27 165 29.0 0.426 22 neg
## 735 2 105 75 0 0 23.3 0.560 53 neg
## 736 4 95 60 32 0 35.4 0.284 28 neg
## 737 0 126 86 27 120 27.4 0.515 21 neg
## 738 8 65 72 23 0 32.0 0.600 42 neg
## 739 2 99 60 17 160 36.6 0.453 21 neg
## 740 1 102 74 0 0 39.5 0.293 42 pos
## 741 11 120 80 37 150 42.3 0.785 48 pos
## 742 3 102 44 20 94 30.8 0.400 26 neg
## 743 1 109 58 18 116 28.5 0.219 22 neg
## 744 9 140 94 0 0 32.7 0.734 45 pos
## 745 13 153 88 37 140 40.6 1.174 39 neg
## 746 12 100 84 33 105 30.0 0.488 46 neg
## 747 1 147 94 41 0 49.3 0.358 27 pos
## 748 1 81 74 41 57 46.3 1.096 32 neg
## 749 3 187 70 22 200 36.4 0.408 36 pos
## 750 6 162 62 0 0 24.3 0.178 50 pos
## 751 4 136 70 0 0 31.2 1.182 22 pos
## 752 1 121 78 39 74 39.0 0.261 28 neg
## 753 3 108 62 24 0 26.0 0.223 25 neg
## 754 0 181 88 44 510 43.3 0.222 26 pos
## 755 8 154 78 32 0 32.4 0.443 45 pos
## 756 1 128 88 39 110 36.5 1.057 37 pos
## 757 7 137 90 41 0 32.0 0.391 39 neg
## 758 0 123 72 0 0 36.3 0.258 52 pos
## 759 1 106 76 0 0 37.5 0.197 26 neg
## 760 6 190 92 0 0 35.5 0.278 66 pos
## 761 2 88 58 26 16 28.4 0.766 22 neg
## 762 9 170 74 31 0 44.0 0.403 43 pos
## 763 9 89 62 0 0 22.5 0.142 33 neg
## 764 10 101 76 48 180 32.9 0.171 63 neg
## 765 2 122 70 27 0 36.8 0.340 27 neg
## 766 5 121 72 23 112 26.2 0.245 30 neg
## 767 1 126 60 0 0 30.1 0.349 47 pos
## 768 1 93 70 31 0 30.4 0.315 23 neg
set.seed(7)
index <- createDataPartition(dataset$diabetes, p=0.80, list=FALSE)
trainSet <- dataset[index, ]
validationSet <- dataset[-index, ]
control <- trainControl(method="repeatedcv", number=10, repeats=3)
metric <- "Accuracy"
set.seed(7)
fit.lda <- train(diabetes~., data=trainSet, method="lda", metric=metric, trControl=control)
fit.cart <- train(diabetes~., data=trainSet, method="rpart", metric=metric, trControl=control)
fit.knn <- train(diabetes~., data=trainSet, method="knn", metric=metric, trControl=control)
fit.svm <- train(diabetes~., data=trainSet, method="svmRadial", metric=metric, trControl=control)
fit.rf <- train(diabetes~., data=trainSet, method="rf", metric=metric, trControl=control)
results <- resamples(list(
LDA=fit.lda,
CART=fit.cart,
KNN=fit.knn,
SVM=fit.svm,
RF=fit.rf
))
summary(results)
##
## Call:
## summary.resamples(object = results)
##
## Models: LDA, CART, KNN, SVM, RF
## Number of resamples: 30
##
## Accuracy
## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## LDA 0.7049180 0.7377049 0.7805394 0.7734620 0.8056584 0.8524590 0
## CART 0.6451613 0.7096774 0.7704918 0.7518949 0.7868852 0.8360656 0
## KNN 0.6393443 0.6897805 0.7317557 0.7315794 0.7741935 0.8548387 0
## SVM 0.6451613 0.7377049 0.7704918 0.7637317 0.8000397 0.8709677 0
## RF 0.6885246 0.7419355 0.7580645 0.7707298 0.8015600 0.8852459 0
##
## Kappa
## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## LDA 0.3154613 0.3920504 0.4865885 0.4736178 0.5488980 0.6536278 0
## CART 0.1367089 0.3319684 0.4364985 0.4248111 0.5197822 0.6197007 0
## KNN 0.1430396 0.2829550 0.3879094 0.3762834 0.4623812 0.6658683 0
## SVM 0.1777188 0.3781122 0.4546616 0.4417620 0.5174114 0.6930693 0
## RF 0.2687697 0.4261566 0.4588719 0.4827568 0.5512552 0.7429259 0
bwplot(results)
densityplot(results, pch="|")
dotplot(results)
splom(results)
diffs <- diff(results)
summary(diffs)
##
## Call:
## summary.diff.resamples(object = diffs)
##
## p-value adjustment: bonferroni
## Upper diagonal: estimates of the difference
## Lower diagonal: p-value for H0: difference = 0
##
## Accuracy
## LDA CART KNN SVM RF
## LDA 0.021567 0.041883 0.009730 0.002732
## CART 1.00000 0.020316 -0.011837 -0.018835
## KNN 0.02598 1.00000 -0.032152 -0.039150
## SVM 1.00000 1.00000 0.06315 -0.006998
## RF 1.00000 1.00000 0.08656 1.00000
##
## Kappa
## LDA CART KNN SVM RF
## LDA 0.048807 0.097334 0.031856 -0.009139
## CART 1.00000 0.048528 -0.016951 -0.057946
## KNN 0.03849 0.99796 -0.065479 -0.106473
## SVM 1.00000 1.00000 0.17208 -0.040995
## RF 1.00000 0.52049 0.03218 1.00000
predictions <- predict(fit.lda, validationSet)
confusionMatrix(predictions, validationSet$diabetes)
## Confusion Matrix and Statistics
##
## Reference
## Prediction neg pos
## neg 85 20
## pos 15 33
##
## Accuracy : 0.7712
## 95% CI : (0.6965, 0.8352)
## No Information Rate : 0.6536
## P-Value [Acc > NIR] : 0.001098
##
## Kappa : 0.4834
##
## Mcnemar's Test P-Value : 0.498962
##
## Sensitivity : 0.8500
## Specificity : 0.6226
## Pos Pred Value : 0.8095
## Neg Pred Value : 0.6875
## Prevalence : 0.6536
## Detection Rate : 0.5556
## Detection Prevalence : 0.6863
## Balanced Accuracy : 0.7363
##
## 'Positive' Class : neg
##