An Optimized Discrete Data Classification Method in <span class="nowrap"><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-0.2723999pt" id="M1" height="11.6718pt" version="1.1" viewBox="-0.0657574 -11.3994 14.5827 11.6718" width="14.5827pt"><g transform="matrix(.017,0,0,-0.017,0,0)"><path id="g113-79" d="M822 650H589L583 622C660 617 677 607 674 561C672 534 664 481 647 390L600 137H596L273 650H126L120 622C176 620 194 615 207 594C221 571 225 557 214 504L161 257C141 166 129 112 121 85C108 42 83 30 29 28L23 0H260L266 28C193 33 173 42 176 89C178 122 186 172 202 255L256 527H259L583 -8H612L690 390C708 481 720 535 728 558C744 603 756 619 816 622L822 650Z"/></g></svg>-</span>Dimensional

<div>The constrained optimization problem of finding a circle in 2D that is closest to all points among all the circle that are constrained to pass through <svg height="11.8239pt" id="M45" style="vertical-align:-3.18147pt" version="1.1" viewbox="-0.0498162 -8.64243 14.937 11.8239" width="14.937pt" 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="M734 -137C662 -100 567 -37 503 8C623 45 724 166 724 333C724 530 575 665 393 665C162 665 42 496 42 319C42 232 74 149 131 87C187 26 281 -9 343 -13C470 -114 547 -148 579 -156C617 -166 676 -172 726 -164L734 -137ZM358 30C254 60 195 186 195 343S263 623 372 623C491 623 571 502 571 303C571 139 512 56 466 37C458 43 449 50 440 56L358 30Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,9.891,3.132)"><path d="M389 0V32C297 38 291 46 291 118V635C234 613 175 595 109 583V556L161 554C203 552 207 547 207 497V118C207 46 201 38 110 32V0H389Z"></path></g></svg> and <svg height="11.8239pt" id="M46" style="vertical-align:-3.18147pt" version="1.1" viewbox="-0.0498162 -8.64243 17.9121 11.8239" width="17.9121pt" 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="M734 -137C662 -100 567 -37 503 8C623 45 724 166 724 333C724 530 575 665 393 665C162 665 42 496 42 319C42 232 74 149 131 87C187 26 281 -9 343 -13C470 -114 547 -148 579 -156C617 -166 676 -172 726 -164L734 -137ZM358 30C254 60 195 186 195 343S263 623 372 623C491 623 571 502 571 303C571 139 512 56 466 37C458 43 449 50 440 56L358 30Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,9.891,3.132)"><path d="M414 144C384 79 371 75 317 75H135L276 221C367 316 408 376 408 465C408 570 327 635 237 635C179 635 131 609 100 575L42 494L67 471C94 510 138 565 205 565C277 565 321 517 321 435C321 348 258 270 195 195C146 137 88 81 33 26V0H411C423 44 433 88 446 135L414 144Z"></path></g><g transform="matrix(.013,0,0,-0.013,14.837,0)"><path d="M113 -12C146 -12 170 11 170 46C170 78 146 103 114 103S58 78 58 46C58 11 82 -12 113 -12Z"></path></g></svg></div>

Computational and Mathematical Methods

fig1

Figure 1

Figure 1: An Optimized Discrete Data Classification Method in <span class="nowrap"><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-0.2723999pt" id="M1" height="11.6718pt" version="1.1" viewBox="-0.0657574 -11.3994 14.5827 11.6718" width="14.5827pt"><g transform="matrix(.017,0,0,-0.017,0,0)"><path id="g113-79" d="M822 650H589L583 622C660 617 677 607 674 561C672 534 664 481 647 390L600 137H596L273 650H126L120 622C176 620 194 615 207 594C221 571 225 557 214 504L161 257C141 166 129 112 121 85C108 42 83 30 29 28L23 0H260L266 28C193 33 173 42 176 89C178 122 186 172 202 255L256 527H259L583 -8H612L690 390C708 481 720 535 728 558C744 603 756 619 816 622L822 650Z"/></g></svg>-</span>Dimensional 

Computational and Mathematical Methods

An Optimized Discrete Data Classification Method in -Dimensional

Figure 1