是什么启发了这个愿望清单请求？
不需要经验模型的数据挖掘“bump hunting”算法。相反，它“耐心地”/递增地搜索输入因素的超级框，以最大化响应。
您希望看到哪些改进？
来自 R：
library<SPAN class="">(</SPAN>prim<SPAN class="">)</SPAN>
library<SPAN class="">(</SPAN>MASS<SPAN class="">)</SPAN>
data<SPAN class="">(</SPAN>Boston<SPAN class="">)</SPAN>
x <SPAN class="">\</SPAN><SPAN class=""><-</SPAN> Boston<SPAN class="">\</SPAN><SPAN class="">[</SPAN><SPAN class="">,</SPAN><SPAN class="">5</SPAN><SPAN class="">:</SPAN><SPAN class="">6</SPAN><SPAN class="">\</SPAN><SPAN class="">]</SPAN>
y <SPAN class="">\</SPAN><SPAN class=""><-</SPAN> Boston<SPAN class="">\</SPAN><SPAN class="">[</SPAN><SPAN class="">,</SPAN><SPAN class="">1</SPAN><SPAN class="">\</SPAN><SPAN class="">]</SPAN>
boston.prim <SPAN class="">\</SPAN><SPAN class=""><-</SPAN> prim.box<SPAN class="">(</SPAN>x<SPAN class="">=</SPAN>x<SPAN class="">,</SPAN> y<SPAN class="">=</SPAN>y<SPAN class="">,</SPAN> threshold.type<SPAN class="">=</SPAN><SPAN class="">1</SPAN><SPAN class="">)</SPAN>
为什么这个想法很重要？
