1) mutual information B-splines
互信息B样条
2) b-quasi mutual information
b-拟互信息
1.
Results Some asymptotic bound for b-quasi fuzzy entropy,b-quasi conditional fuzzy entropy,b-quasi mutual information and some meaning results are obtained.
结果得到b-拟模糊熵、b-拟条件模糊熵、b-拟互信息的渐近界的定义和一些良好的性质及定理。
3) conditional mutual information
条件互信息
1.
BSNBC classifying algorithm measured by conditional mutual information;
条件互信息度量BSNBC分类学习算法
2.
Improved feature selection algorithm with conditional mutual information;
一种改进的基于条件互信息的特征选择算法
4) WMI
词条互信息
1.
A new text clustering method based on WMI(words mutual information) statistical reduction dimension approach and Kohonen network(SOFM network) was proposed.
提出了一种基于词条互信息(WM I)值的统计降维和Kohonen网络(SOFM网)相结合的文本聚类方法,WM I值的方法侧重考虑文本特征项之间的互信息进行降维,可提高特征选择的效率,并使其更趋实用化。
5) Bernstein-Bézier spline
B-B样条
6) B-spline
B-样条
1.
Terrain Reconstruction Algorithm Based on Bi-cubic B-spline Interpolation;
基于双三次B-样条插值的大地形重构
2.
Four-degree B-spline method for constructing theoretical treasury yield curves;
四次B-样条法构造国债收益率曲线
3.
Calculating Method of Contraction Operators in Fractal Interpolation Based on the B-spline;
基于B-样条分形插值的垂直尺度因子的计算方法
补充资料：互信息
见信息量。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条