If two sets are linearly separable (LS), then there exists a single layer perceptron feedforward neural network that classifies them. We propose three methods for testing linear separability. The first method is
Instance-based classifiers, such as k-NN, can overcome the challenge of “linearly inseparable” in malicious URLs detection. k-NN does not pursuit linear separability and only uses the labels of the surrounding points. But unlike SVM, which can learn a vector that rescales the original feature...
A rule 90-based FPGA implementation of a ReCA model for the application of handwritten digit recognition based on the MNIST dataset is presented in [52]. Even though their implementation does not reach the classification accuracy of current state-of-the-art Convolutional Neural Network (CNN)-based...
As a result, estimating mapping matrices W based on a compromise between generative and discriminative terms allows capturing both the inherent input information while forcing the samples to be projected into a space with higher class separability. 5 Conclusion This paper discusses the linear projection...
•Issues:VCdimension,linearseparability,featurespace,multipleclass. Lecture6(draft)5 MainIdea •Givenasetofdatapointswhichbelongtoeitheroftwoclasses,anSVM findsthehyperplane: -leavingthelargestpossiblefractionofpointsofthesameclassonthe sameside. -andmaximizingthedistance of either class from the hyperpla...
A key problem in Binary Neural Network learning is to decide bigger linear separable subsets. In this paper we prove some lemmas about linear separability. Based on these lemmas, we propose Multi-Core Learning (MCL) and Multi-Core Expand-and-Truncate Learning (MCETL) algorithms to construct ...
Class of separabilityIf two sets are linearly separable (LS), then there exists a single layer perceptron feed- forward neural network that classifies them. We propose three methods for testing linear separability. The first method is based on the notion of convex hull, the second on a halting...
D. A. Elizondo, J. O. de Lazcano-Lobato, R. Birkenhead, "Choice effect of linear separability testing methods on constructive neural network algorithms: An empirical study", Expert Systems with Applications, Vol. 38, pp. 2330-2346, 2011....
A modification of the softmax loss function, which is called Angular softmax (Zhao, Xu, & Cheng, 2019), was recently proposed as an explicit regularization technique, trying to increase the inter-class separability by distancing between class centers. Although this method, theoretically, leads to...
2.9. Specifically, LDA formulates the problem in terms of scatter matrices (scatter and variance both measure the spread of data around the mean; however, scatter is just on a different scale than variance). The assumption is that class separability is higher if the “projected” class means ...