官术网_书友最值得收藏!

One-vs-one

The alternative to one-vs-all is training a model for each pair of classes. The complexity is no longer linear (it's O(n2) indeed) and the right class is determined by a majority vote. In general, this choice is more expensive and should be adopted only when a full dataset comparison is not preferable.

If you want to learn more about multiclass strategies implemented by scikit-learn, visit 
http://scikit-learn.org/stable/modules/multiclass.html.
主站蜘蛛池模板: 乌鲁木齐县| 永年县| 盐源县| 科技| 轮台县| 年辖:市辖区| 平原县| 宁晋县| 洪湖市| 邯郸县| 新民市| 南川市| 平顺县| 富源县| 西盟| 徐汇区| 华容县| 全州县| 乳源| 济宁市| 大渡口区| 伊春市| 高淳县| 德惠市| 寿光市| 昌邑市| 黄浦区| 高雄县| 金平| 察隅县| 韩城市| 高要市| 监利县| 临安市| 荥经县| 宿迁市| 紫阳县| 平顺县| 华宁县| 扬中市| 报价|