Abstract

One of the research topics in machine learning is incremental machine learning. The ever-increasing data size and variety in response to the limited memory and processing power make incremental learning approaches mandatory. In this study, focal changes in the data are determined for incremental classification algorithms by defining the general framework of the incremental machine learning approach. In addition, along with the theoretical definition of incremental machine learning, the existing machine learning algorithms that are suitable for incremental machine learning are defined. It is mentioned that in terms of which features of these algorithms are suitable for incremental learning. This study provides a detailed definition for researchers who will work on incremental machine learning issues, as well as defines the incremental classification characteristics and gives information about the focus changes in the data.

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