Sentence examples for lower approximation from inspiring English sources

We can approximate X using only the information contained in B by constructing lower approximation and upper approximation of X on the following way: underline{B}(X)=left{xin U B x)subseteq Xright} (6) overline{B} X =left{xin U B x cap Xne varnothing right} (7).

In this case, we obtain dispersed approximate sets representing the bnodes, i.e., sets with an empty lower approximation (γ Ainf(X i,X j )=0) and an upper approximation equal to the set universe (γ Asup(X i,X j )=|U|) [7], as shown in Figure 14b.

Each data sample is randomly assigned to one lower approximation.

Similarly, a tight lower approximation can be applied to discover a set of concepts reinforcing the lower approximation, i.e., contexts which preserve the lower approximation in a similarity relation of a higher step.

At the same time, upper approximation and lower approximation are defined under this improved relation.

Fig. 2 Boundary, Upper and Lower Approximation of a set X.

This method introduces upper approximation and lower approximation into k-means clustering algorithm.

Rough sets can be defined by upper approximation and lower approximation.

However, while the lower approximation is defined as crisp, the boundary area is fuzzy.

If the value of d x,t i )−dmin(x) ≥ λ, the sample x is subject to the lower approximation of its cluster, where λ denotes the threshold for determining upper and lower approximation.

This result shows that the context {B} is already enough to be used in the lower approximation of Medium.