Jen-Cheng Chen

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In this paper, we propose a new feature evaluation method that forms the basis for feature ranking and selection. The method starts by generating a number of feature subsets in a random fashion and evaluates features based on the derived subsets. It then proceeds in a number of stages. In each stage, it inputs the features whose ranks in the previous stage(More)
The neural networks are successfully applied to many applications in different domains. However, due to the results made by the neural networks are difficult to explain the decision process of neural networks is supposed as a black box. The explanation of reasoning is important to some applications such like credit approval application and medical(More)
The principal object of this paper is to develop a neural network model, which can simulate the plasma enhanced chemical vapor deposition (PECVD) process in TFT-Array procedure. Then the Boolean logic rules are extracted from the trained neural network in order to establish a knowledge base of expert system. The input data of neural network was collected(More)
In this paper, we propose a new feature evaluation method that forms the basis for feature ranking and feature selection. The method starts by generating a number of feature subsets in a random fashion and evaluates features based on the derived subsets. It then proceeds in a number of stages. In each stage, it inputs the features whose ranks in the(More)
For school children users, mostly less skilled in keying or unfamiliar with the keyboard, most key legends are important since a major proportion of the time is spent looking at the keyboard. The key legends need therefore to be as explicit and easy to understand as possible. In the initial experiment, we sampled twenty-one school children users to simulate(More)
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