Classification is an important technique in the field of Data Mining and Machine Learning. The classifier can predict the class of unknown data based on their given attribute values. In ubiquitous computing environment, a great deal information can be obtained from various sensors. However, with the time going on, new sensor may be recruited. The recruited new sensors may bring new outcomes to the existing attribute. How to handle the new outcomes is a difficult issue. This paper first presents the problem and meanwhile a new method for handling new outcomes is proposed. The old rule is generated from the old data with fewer outcomes and modified and combined with the new data smoothly. In the method, the old rule can improve the performance of classifier constructed only from the new data set. The experiments show that the proposed approach is effective in handling new outcomes.
['Yingrong Li', 'Anastasiya Kolesnikova', 'Won Don Lee']
A new classification approach for handling new outcomes