| 1. | Study on the multiclass classifying based on the one - class classification
基于一类分类方法的多类分类研究 |
| 2. | Study on multiclass text categorization based on support vector machine
基于支持向量机的多元文本分类研究 |
| 3. | The multiclass svm methods based on binary tree are proposed
摘要提出一种新的基于二叉树结构的支持向量( svm )多类分类算法。 |
| 4. | Numerical experiment results show that the multiclass svm methods are suitable for practical use
实验结果表明，该算法具有一定的优越性。 |
| 5. | The new methods can resolve the unclassifiable region problems in the conventional multiclass svm methods
该算法解决了现有主要算法所存在的不可分区域问题。 |
| 6. | As described in chapter 2 of the dungeon master ' s guide , characters who qualify can multiclass with a prestige class when they advance in level
就如同《地下城主指南》第二章所述，符合条件的人物可以在升级时兼职进阶职业。 |
| 7. | Multiclass characters treat all skills gained from any of their classes as class skills . the character level determines a skill ' s maximum rank
兼职人物的所有职业中的本职技能都是该人物的本职技能。人物等级决定其技能等级最大值。 |
| 8. | If a skill is not a class skill for any of a multiclass character ' s classes , the maximum rank for that skill is one - half the maximum for a class skill
如果某技能不是兼职人物任何职业的本职技能，那么该技能的最大级数是本职技能最大级数的一半。 |
| 9. | Support vector machines ( svms ) for binary classification have been solved perfectly , but svms for multiclass classification and regressive ability need to be researched and improved further
支持向量机对二类划分问题已解决得非常好，但其对多类划分问题及回归的能力仍有待进一步研究和改善。 |
| 10. | In proc . neural information processing systems conference , vancouver and whistler , bc , canada , 2003 , pp . 833 - 840 . 9 dekel o , singer y . multiclass learning by probabilistic embeddings
因此，特征数据的降维方法，即将高维的特征数据如何进行简化投射到低维空间中再进行处理，成为了当前数据驱动的计算方法研究热点之一。 |
