separable degree

separable degree的基本解释

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可分度

与separable degree相关的网络例句 [注：此内容来源于网络，仅供参考]

Post-secondary (Sub-degree course)（专上教育: Including all Higher Certificate/ Higher Diploma/ Professional Diploma/ Associate Degree/ Pre-Associate Degree/ Endorsement Certificate/ Associateship or equivalent courses in Universities/ Vocational Training Council, other sub-degree courses in Universities funded by University Grants Committee, Higher Certificate/ Higher Diploma/ Professional Diploma/ Associate Degree/ Pre-Associate Degree or equivalent courses in former Polytechnics/ other statutory or approved Postsecondary Colleges, Higher Diploma/ Professional Diploma/ Associate Degree/ Pre-Associate Degree or equivalent courses in other colleges providing postsecondary courses, sub-degree courses in Hong Kong Institute of Education, Sub-degree level nurse training courses/ dental training courses, Distance learning sub-degree level courses and other sub-degree level courses

包括大学／职业训练局的高级证书／高级文凭／专业文凭/副学士/副学士先修/增修证书/院士衔或同等课程、由大学资助委员会资助的其它大学非学位课程、前理工学院/其它法定或认可的专上学院的高级证书/高级文凭/专业文凭/副学士/副学士先修或同等课程、其它专上学院开设的高级文凭/专业文凭/副学士/副学士先修或同等课程、香港教育学院的非学位课程、护士训练非学位课程、牙科训练非学位课程及遥距非学位课程。

A new SVM is presented in this paper to solve the approximately linear separable problem of pattern recognition:First,we transform the two convex hulls which are made up of the approximately separable training set to make them separable;Second,we can figure out a separating hyperplane by halving the nearest points method or maximal margin method;Then,we get the approximately linear SVM by solving the dual problem of maximal margin method.

对模式分类中的近似线性可分问题提出了一种新的近似线性支持向量机：先对近似线性分类中的训练集所形成的两类凸壳进行了相似变形，使变形后的凸壳线性可分，再用平分最近点和最大间隔法求出理想的分划超平面，然后再通过求解最大间隔法的对偶问题得到基于相似压缩的近似线性SVM。

Ln this paper, a new learning method is presented which is based on analyzing a set of linear separable structures. The most important benefit of this method is all binary neurons belong to one or more types of linear separable structure sets. If those linear separable structure sets have clear logical meaning, the whole knowledge of binary neural networks can be dug out.

该文提出了一种基于线性可分结构系结构分析的学习算法，采用这种方法对布尔空间的样本集合进行学习，得到的二进神经网络隐层神经元都归属于一类或几类线性可分结构系，只要这几类线性可分结构系的逻辑意义是清晰的，就可以分析整个学习结果的知识内涵。

与separable degree相关的网络解释 [注：此内容来源于网络，仅供参考]

separable degree：分离度

separable closure 可分闭包 | separable degree 分离度 | separable element 可分元

separable degree：可分次数

可分[离]规划|separable programming | 可分次数|separable degree | 可分代数|separable algebra