Mixed sample data augmentation是一种在机器学习中常用的技术,它通过结合不同样本的特征来创建新的训练样本,从而提高模型的泛化能力和鲁棒性。以下是关于mixed sample...
A 'Sample Distribution' refers to the distribution of a dataset that is obtained by collecting and converting data into numerical values. It helps in understanding the characteristics of the data, such as center, spread, modality, and shape, which are essential for further analysis and feature ex...
For example, the OSD dataset, with no more than one hundred samples is eclipsed by the TOD dataset, where tens of thousands of samples are present. That fact was taken into consideration in order to obtain an unbiased analytic result. Consequently, the maximum evaluation size was set at 1000...
Then, a sample dataset is selected with the negative and positive sample ratio of 1:1. An optimal training sample is selected by tenfold cross-validation, while the testing sample is randomly selected from the sample dataset comprising 30% of the sample dataset. A logistic regression (LR) ...
Sample multiplexing facilitates scRNA-seq by reducing costs and identifying artifacts such as cell doublets. However, universal and scalable sample barcoding strategies have not been described. We therefore developed MULTI-seq: multiplexing using lipid-t
On average, the word-initial consonants in the simulated dataset are expected to be around ~13 ms longer (~106 ms) than consonants in other positions (~93 ms). Full posterior predictive checks according to the Bayesian Analysis Reporting Guidelines42 are presented in Supplementary ...
For regression analysis, 75% and 25% of the rest of samples were selected as the calibration and prediction sets. The steps of random frog proposed by Li et al.,24 are described as follows for seeking out the hardness-specific wavelengths: (1) configure the appropriate parameters: the ...
Logit Regression: Statsample::Regression::Binomial::Logit Probit Regression: Statsample::Regression::Binomial::Probit Factorial Analysis algorithms on Statsample::Factor module. Classes for Extraction of factors: Statsample::Factor::PCA Statsample::Factor::PrincipalAxis ...
Dataset The proposed framework for sample network exploration (Methods) was used to analyze microarray data from “the HD study” [14]. These data were generated from brain samples of patients with HD (n = 44 individuals) and unaffected controls (n = 36 individuals, matched for age...
Section 4.1 presents the models for user behaviors, including movement behavior and calling behavior. Section 4.1 also describes both the synthetic dataset and the real dataset. Section 4.2 presents experimental results. Finally, the RUMP sensitivity analysis is given in Section 4.3. Conclusions User ...