Clustering Ensemble Technology Based on Granular Computing to Extract Cervical Cancer Predictors

<div>(a) Changes of <svg height="11.5564pt" id="M200" style="vertical-align:-2.26807pt" version="1.1" viewbox="-0.0498162 -9.28833 41.2032 11.5564" width="41.2032pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M828 650H570L564 622C646 614 650 609 634 524L604 366H253L281 524C296 608 308 615 382 622L388 650H132L126 622C211 615 214 609 198 524L121 122C106 42 102 35 23 28L17 0H276L282 28C196 35 191 40 206 122L243 324H597L559 123C544 42 537 35 452 28L446 0H710L716 28C632 35 628 43 643 122L719 524C735 610 741 615 822 622L828 650Z"></path></g><g transform="matrix(.013,0,0,-0.013,10.923,0)"><path d="M300 -147C201 -63 143 98 143 270S200 602 300 686L282 710C136 610 70 450 70 271V270C70 89 136 -72 282 -170L300 -147Z"></path></g><g transform="matrix(.013,0,0,-0.013,15.421,0)"><path d="M517 162C503 123 484 89 467 68C445 42 417 34 341 34C291 34 256 35 237 47C219 60 213 82 213 129V317H308C395 317 402 311 415 240H444V431H415C403 364 398 356 307 356H213V584C213 613 215 616 246 616H322C394 616 421 609 435 587C448 566 458 544 467 502L496 506C493 557 488 625 488 650H42V622C120 616 128 612 128 523V125C128 42 120 34 29 28V0H511C520 31 540 125 546 158L517 162Z"></path></g><g transform="matrix(.013,0,0,-0.013,22.805,0)"><path d="M95 130C70 130 46 113 46 88C46 72 54 64 59 64C93 55 121 33 121 -3C121 -41 93 -68 44 -88L55 -117C117 -98 186 -56 186 22C186 91 131 130 95 130Z"></path></g><g transform="matrix(.013,0,0,-0.013,27.948,0)"><path d="M655 0V28C585 35 562 50 517 120C469 193 414 280 360 366C427 469 460 516 481 545C526 604 545 614 619 622V650H390V622C457 614 462 604 438 560C411 511 381 463 339 398C295 466 258 523 225 580C210 606 211 615 272 622V650H26V622C97 614 111 603 153 538C188 482 235 408 288 324C200 188 148 116 124 85C96 47 64 34 7 28V0H236V28C169 36 164 46 188 89C220 148 262 217 310 291C372 193 417 118 442 77C461 44 454 35 392 28V0H655Z"></path></g><g transform="matrix(.013,0,0,-0.013,36.463,0)"><path d="M275 270C275 450 212 609 64 710L45 686C145 604 203 442 203 270S147 -63 45 -147L64 -170C213 -68 275 89 275 270Z"></path></g></svg> with the clustering process. (b) Changes in the absolute value of difference between two adjacent points of <span class="nowrap"><svg height="11.5564pt" id="M201" style="vertical-align:-2.26807pt" version="1.1" viewbox="-0.0498162 -9.28833 41.2032 11.5564" width="41.2032pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M828 650H570L564 622C646 614 650 609 634 524L604 366H253L281 524C296 608 308 615 382 622L388 650H132L126 622C211 615 214 609 198 524L121 122C106 42 102 35 23 28L17 0H276L282 28C196 35 191 40 206 122L243 324H597L559 123C544 42 537 35 452 28L446 0H710L716 28C632 35 628 43 643 122L719 524C735 610 741 615 822 622L828 650Z"></path></g><g transform="matrix(.013,0,0,-0.013,10.923,0)"><path d="M300 -147C201 -63 143 98 143 270S200 602 300 686L282 710C136 610 70 450 70 271V270C70 89 136 -72 282 -170L300 -147Z"></path></g><g transform="matrix(.013,0,0,-0.013,15.421,0)"><path d="M517 162C503 123 484 89 467 68C445 42 417 34 341 34C291 34 256 35 237 47C219 60 213 82 213 129V317H308C395 317 402 311 415 240H444V431H415C403 364 398 356 307 356H213V584C213 613 215 616 246 616H322C394 616 421 609 435 587C448 566 458 544 467 502L496 506C493 557 488 625 488 650H42V622C120 616 128 612 128 523V125C128 42 120 34 29 28V0H511C520 31 540 125 546 158L517 162Z"></path></g><g transform="matrix(.013,0,0,-0.013,22.805,0)"><path d="M95 130C70 130 46 113 46 88C46 72 54 64 59 64C93 55 121 33 121 -3C121 -41 93 -68 44 -88L55 -117C117 -98 186 -56 186 22C186 91 131 130 95 130Z"></path></g><g transform="matrix(.013,0,0,-0.013,27.948,0)"><path d="M655 0V28C585 35 562 50 517 120C469 193 414 280 360 366C427 469 460 516 481 545C526 604 545 614 619 622V650H390V622C457 614 462 604 438 560C411 511 381 463 339 398C295 466 258 523 225 580C210 606 211 615 272 622V650H26V622C97 614 111 603 153 538C188 482 235 408 288 324C200 188 148 116 124 85C96 47 64 34 7 28V0H236V28C169 36 164 46 188 89C220 148 262 217 310 291C372 193 417 118 442 77C461 44 454 35 392 28V0H655Z"></path></g><g transform="matrix(.013,0,0,-0.013,36.463,0)"><path d="M275 270C275 450 212 609 64 710L45 686C145 604 203 442 203 270S147 -63 45 -147L64 -170C213 -68 275 89 275 270Z"></path></g></svg>.</span></div>

Mathematical Problems in Engineering

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Figure 4

Figure 4: Clustering Ensemble Technology Based on Granular Computing to Extract Cervical Cancer Predictors 