We use a random subspace of AdaBoost.M1 to combine the scores of the best fingerprint matchers automatically selected among the competitors of FVC2004, and we study the performance when a different number of competitors are involved in the fusion.
Random allocation was accomplished using a random number table.
In addition, a random subspace ensemble using a combination of SVM, multilayer perceptron (MLP) neural network and an extended k-nearest neighbors (k-NN), called extended nearest neighbor (ENN), is developed for the EEG and electrocorticography (ECoG) big data problem.
Therefore, we used a modified random subspace method [ 38], and proposed an FSS generation strategy, which is described below.
Second, we constructed a series of support vector machines (SVMs) with a random subspace of the features.
Recently, Guan et al. [14] proposed a random subspace method to deal with the covariate of clothing.
Based on this, Ho raised a random subspace method (RSM) and constructed a forest with the idea of RSM and the decision tree [31].
At each node, a random subspace of all SNPs is chosen to determine the best split to generate the children nodes.
The main characteristic of RF is that the correlation between individual base learners is reduced by choosing the best predictors in a random subspace of the training data.
We used a random-effects model.
