Selecting Classification Methods for Small Samples of Next-Generation Sequencing Data
Frontiers in Genetics, 2021 Next-generation sequencing has emerged as an essential technology for the quantitative analysis of gene expression. In medical research, RNA sequencing (RNA-seq) data are commonly used to identify which type of disease a patient has.
Jiadi Zhu +5 more
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Pair-Copula Constructions for Financial Applications: A Review
Econometrics, 2016 This survey reviews the large and growing literature on the use of pair-copula constructions (PCCs) in financial applications. Using a PCC, multivariate data that exhibit complex patterns of dependence can be modeled using bivariate copulae as simple ...
Kjersti Aas
doaj +1 more source
Learning to Avoid Obstacles With Minimal Intervention Control
Frontiers in Robotics and AI, 2020 Programming by demonstration has received much attention as it offers a general framework which allows robots to efficiently acquire novel motor skills from a human teacher.
Anqing Duan +10 more
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Learning and teaching statistical investigations: a case study of a prospective teacher [PDF]
, 2014 More than a collection of tools to deal with problems, statistics provides a comprehensive framework to think about the world. One way of using it is doing statistical investigations (SI).
Ponte, João Pedro da, Santos, Raquel
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Statistical learning in infants [PDF]
Proceedings of the National Academy of Sciences, 2002 Statistical learning has become the subject of some considerable debate within cognitive psychology (1, 2). The debate reached particular prominence with the advent of sophisticated computational models of such learning based on neurally inspired notions of spreading activation within highly distributed systems of interacting units, so-called neural ...
openaire +2 more sources
Expanding the notion of global learning: Turkish-Dutch teens’ networked configurations for learning [PDF]
, 2020 Digital technology facilitate interactions between learners and resources at a global level. New learner prototypes are therefore proposed, such as the notion of the global learner.
Ünlüsoy, Asli +5 more
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Active Learning with Statistical Models. [PDF]
Journal of Artificial Intelligence Research, 1995 For many types of machine learning algorithms, one can compute the statistically `optimal' way to select training data. In this paper, we review how optimal data selection techniques have been used with feedforward neural networks. We then show how the same principles may be used to select data for two alternative, statistically-based ...
David A. Cohn +2 more
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High-dimensional statistical learning: Roots, justifications, and potential machineries [PDF]
, 2016 High-dimensional data generally refer to data in which the number of variables is larger than the sample size. Analyzing such datasets poses great challenges for classical statistical learning because the finite-sample performance of methods developed ...
Zollanvari, Amin, Amin Zollanvari
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Multi-decadal streamflow projections for catchments in Brazil based on CMIP6 multi-model simulations and neural network embeddings for linear regression models [PDF]
Hydrology and Earth System SciencesA linear regression model is developed to link anomalies of streamflow to anomalies of precipitation amounts and temperature with the goal of making multi-decadal streamflow projections based on CMIP6 multi-model simulations.
M. Scheuerer +5 more
doaj +1 more source
Multivariate Adaptive Regression Splines Enhance Genomic Prediction of Non-Additive Traits
AgronomyThe present work used Multivariate Adaptive Regression Splines (MARS) for genomic prediction and to study the non-additive fraction present in a trait. To this end, 12 scenarios for an F2 population were simulated by combining three levels of broad-sense
Maurício de Oliveira Celeri +6 more
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