Blar i Brage NMBU på forfatter "Indahl, Ulf Geir"
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Much faster cross‐validation in PLSR‐modelling by avoiding redundant calculations
Liland, Kristian Hovde; Stefansson, Petter; Indahl, Ulf Geir (Peer reviewed; Journal article, 2020) -
Non-ferrous metal price forecasting with Recurrent Neural Networks : how do they perform when forecasting multiple timesteps ahead?
Bø, Martin (Master thesis, 2021)This thesis aims to forecast the daily price of aluminum, copper and zinc from the London Metal Exchange five days ahead based on prices the previous five days using different recurrent neural networks. A “last-known ... -
Non-linear shrinking of linear model errors
Helin, Runar; Indahl, Ulf Geir; Tomic, Oliver; Liland, Kristian Hovde (Journal article; Peer reviewed, 2023) -
On the application of machine learning techniques for phenotypic classification and clustering of heart failure patients
Adrik, Samir (Master thesis, 2018)In this thesis, we attempt to investigate how well various clustering algorithms (hierarchical clustering, k-means and expectation–maximization) perform in producing phenotypically distinct clinical patient groups (i.e. ... -
Orders of magnitude speed increase in Partial Least Squares feature selection with new simple indexing technique for very tall data sets
Stefansson, Petter; Indahl, Ulf Geir; Liland, Kristian Hovde; Burud, Ingunn (Peer reviewed; Journal article, 2019)Feature selection is a challenging combinatorial optimization problem that tends to require a large number of candidate feature subsets to be evaluated before a satisfying solution is obtained. Because of the computational ... -
Preprocessing of spectral data in the extended multiplicative signal correction framework using multiple reference spectra
Skogholt, Joakim; Liland, Kristian Hovde; Indahl, Ulf Geir (Journal article; Peer reviewed, 2018) -
Press ‘run’ to improve mathematical expertice (PRIME)
Munthe, Morten (PhD Thesis;2022:55, Doctoral thesis, 2022)Press Run to Increase Mathematical Expertise (PRIME) investigates the implementation of programming in the mathematics classroom in upper secondary schools in Norway through the lens of designing mathematical programming ... -
RENT—Repeated Elastic Net Technique for Feature Selection
Jenul, Anna Selina; Schrunner, Stefan; Liland, Kristian Hovde; Indahl, Ulf Geir; Futsæther, Cecilia Marie; Tomic, Oliver (Peer reviewed; Journal article, 2021) -
SAnE: Smart Annotation and Evaluation Tools for Point Cloud Data
Arief, Hasan Asyari; Arief, Mansur Maturidi; Zhang, Guilin; Liu, Zuxin; Bhat, Manoj; Indahl, Ulf Geir; Tveite, Håvard; Zhao, Ding (Peer reviewed; Journal article, 2020)Addressing the need for high-quality, time efficient, and easy to use annotation tools, we propose SAnE, a semiautomatic annotation tool for labeling point cloud data. The contributions of this paper are threefold: (1) we ... -
Selection of principal variables through a modified Gram–Schmidt process with and without supervision
Skogholt, Joakim; Liland, Kristian Hovde; Næs, Tormod; Smilde, Age K.; Indahl, Ulf Geir (Peer reviewed; Journal article, 2023)In various situations requiring empirical model building from highly multivariate measurements, modelling based on partial least squares regression (PLSR) may often provide efficient low-dimensional model solutions. In ... -
The canonical partial least squares approach to analysing multiway datasets—N-CPLS
Liland, Kristian Hovde; Indahl, Ulf Geir; Skogholt, Joakim; Mishra, Puneet (Peer reviewed; Journal article, 2022) -
The O-PLS methodology for orthogonal signal correction—is it correcting or confusing?
Indahl, Ulf Geir (Journal article; Peer reviewed, 2017) -
Variable selection models for genomic selection using whole-genome sequence data and singular value decomposition.
Meuwissen, Theo; Indahl, Ulf Geir; Ødegård, Jørgen (Journal article; Peer reviewed, 2017)