One of the basic issues in pattern recognition is to calculate the boundary between different categories.In this paper

we propose a novel method for that based on computational geometry named active expansion.At first

we quantize the description space.And then term the set as base and non-base points according their distribution

by active expanding for base points

any point in the whole space could express the category information and the boundary is obtained.Using this method

we design the scatter classifier which incorporates the active expansion with combining feature attribute of scatter plot

that mapping the data from low dimension to high dimension and conforming a visual combing classifier.The experiments against UCI datasets show that performance of the novel classifier has been equivalent to the popular classifiers

and outweigh in some dataset.