Web9 de abr. de 2024 · Such high-dimension, low sample size (HDLSS) data often cause computational challenges in biological data analysis. A number of least absolute … Web3 de jan. de 2015 · Low Sample Size (HDLSS) datasets, also known as large p small n data, s ince for this type of data, n ≪ p, i.e., n is much less than p . Data sets of this type are very common these days ...
Deep Neural Networks for High Dimension, Low Sample Size Data
Web24 de jun. de 2024 · Abstract: In this paper, we propose a new method to perform data augmentation in a reliable way in the High Dimensional Low Sample Size (HDLSS) … WebHigh dimensional small sample sized (HDLSS) datasets are datasets which contain many features but a limited number of samples. High dimensional low sample size datasets are commonly found in microarray data and medical imaging (Hall et al.). Most algorithms were not created with high dimensional low sample size data in mind. Due to this, … fob and foc
On perfect clustering of high dimension, low sample size data
Web29 de dez. de 2016 · Popular clustering algorithms based on usual distance functions (e.g., Euclidean distance) often suffer in high dimension, low sample size (HDLSS) … Web27 de ago. de 2024 · Download a PDF of the paper titled Feature Selection from High-Dimensional Data with Very Low Sample Size: A Cautionary Tale, by Ludmila I. … WebDespite the popularity of high dimension, low sample size data analysis, there has not been enough attention to the sample integrity issue, in particular, a possibility of outliers in the data. A new outlier detection procedure for data with much larger dimensionality than the sample size is presented. fob and fca