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Learning strategy for changes of conceptual bias.
| Content Provider | CiteSeerX |
|---|---|
| Author | Inuzuka, Nobuhiro Yamada, Taichi Ishii, Naohiro |
| Abstract | All aspects of an Inductive Learning framework can bias the inductive learning process. If the bias is not selected appropriately, the process will not make a success. To find an appropriate bias, we must design a learning strategy following changes of conceptual bias. In this paper, to solve the problem following changes of bias efficiently, we developed a learning strategy based on the Version Space Method. Our strategy maintains attribute values excluded by negative examples and ones included by positive examples, while the Version Space Method maintains hypotheses. Then, we show how it follows changes of bias, and show its correctness. Furthermore, we compare our method with the Version Space Method in time complexity. 1 Introduction In order to present an Inductive Learning method, we must specify some factors, such as domain space, hypotheses space, and Inductive Inference strategy[1]. We get one framework of Inductive Learning by specifying these. On the other hand, the framewo... |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Conceptual Bias Version Space Method Learning Strategy Appropriate Bias Domain Space Inductive Learning Attribute Value Inductive Learning Framework Inductive Learning Method Positive Example Negative Example Inductive Learning Process Time Complexity Inductive Inference Strategy |
| Content Type | Text |
