Support vector domain description(SVDD) is very suitable for testing a single anomaly point and is inadequate
for testing the whole testing dataset. Based on SVDD, the algorithm of minimum enclosing ball for domain adaptation(MEB-
DA) is proposed. In order to achieve the rapid calculation for large datasets, an algorithm named center constrained minimum
enclosing ball for domain adaptation(CCMEB-DA) is proposed. By calculating the center of each dataset, the dataset is
corrected and the similarity of data is identified between different domains, which shows a good adaptability. The proposed
method is applied to the fields of wireless fidelity(WIFI) indoor positioning and face detection, and the obtained experimental
results show the effectiveness of the proposed algorithm.