1. Data set size, dimensionality and sparsity have been identified as aspects that make cluster more difficult. 数据集合的大小,数据的维数和数据的稀疏性都是制约聚类的不同方面。
2. We construct the sparse eigenvalue by means of the sparsity of polynomial equations in this paper, and prove its equivalence theorem. 利用多项式方程组的稀疏性构作相应的特徵值,给出并证明其等价性定理。
3. The sparsity and the problem of the curse of dimensionality of high-dimensional data, make the most of traditional clustering algorithms lose their action in high-dimensional space. 高维数据的稀疏性和“维灾”问题使得多数传统聚类算法失去作用,因此研究高维数据集的聚类算法己成为当前的一个热点。
英英解释
n.
1. the property of being scanty or scattered; lacking denseness