… In these experiments, I will compare accuracies of forests built by my subspace method to
those built by such training set subsampling methods. The random subspace method is a …

… Abstract: Recently bagging, boosting and the random subspace method have become …
sizes, while bagging and the random subspace method are useful for critical training sample sizes…

… In order to overcome this difficulty we proposed a new method based on random subspace
selection (RSM). A multivariate search technique is applied on a subspace randomly …

… Instead of obtaining random subspaces, we search subspaces that optimize the … method
is shown in Algorithm 2. We have called this method Not so Random Subspace Method …

… and random subspace version of the same learning algorithm using a voting methodology…
We performed a comparison with simple bagging, boosting and random subspace method …

… In this paper, we propose a novel method, called semi-random subspace (Semi-RS), to …
methods [13], [14], [15], [21] and RSM, we propose a semi-random subspace (Semi-RS) method …

… randomized approaches is not completely understood. We provide new theoretical results
which suggest that random subspace methods … approaches to construct a random subspace. …

… As to the base learners used to train classifiers in the random subspaces, we have many …
we choose the random subspaces of the feature space, if the dimensionality of the subspaces is …

… such as bagging, boosting and the random subspace method. When applying them to linear
… in the data feature set on the performance of the random subspace method and bagging. …

… have shown that the random subspace method can be used … We examine the effects of
several parameters of the method by … an application of the random subspace method to k-nearest-…