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Neural network tree (NNTree) is a decision tree (DT) in which each internal node contains a neural network (NN). Experimental results show that the performance of the NNTrees is usually better than that of the traditional univariate DTs. In addition, the NNTrees are more usable than the single model fully connected NNs because their structures can be determined automatically in the induction process...
Neural network tree (NNTree) is a hybrid model for machine learning. So far, we have proposed an efficient algorithm for inducing NNTrees, and verified through experiments that NNTrees are efficient and effective for solving different pattern recognition problems. However, for problems like text categorization, induction of NNTrees can be very computationally expensive. To solve this problem, we have...
Neural network tree (NNTree) is a hybrid model for machine learning. Compared with single model fully connected neural networks, NNTrees are more suitable for structural learning, and faster for decision making. To increase the realizability of the NNTrees, we have tried to induce more compact NNTrees through dimensionality reduction. So far, we have used principal component analysis (PCA) and linear...
Pose recognition is important in many practical applications. For example, a driver assistance system can detect if the driver is tired, sleepy, or careless from the poses. A pet robot can detect certain behavior patterns of the human user. The main purpose of this study is to develop a driver assistance system that can protect the drivers from careless accidents. As the first step, we propose a system...
An NNC-tree is a decision tree (DT) with each non-terminal node containing a nearest neighbor classifier (NNC). Compared with the axis-parallel decision trees (APDTs), NNC-trees are more comprehensible for large problems, because the decision rules corresponding to the trees are simpler. Currently, the author has proposed an algorithm for inducing NNC-trees based on the R4-rule. However, compared...
Neural network tree (NNTree) is a decision tree (DT) with each non-terminal node containing an expert neural network (ENN). Generally speaking, NNTrees can outperform standard axis-parallel DTs because the ENNs can extract more complex features. However, induction of multivariate DTs is very difficult. Even if each non-terminal node contains a simple oblique hyperplane, finding the optimal test function...
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