Investigation of prediction accuracy and the impact of sample size, ancestry, and tissue in transcriptome‐wide association studies
Sign Up to like & getrecommendations! Published in 2020 at "Genetic Epidemiology"
DOI: 10.1002/gepi.22290
Abstract: In transcriptome‐wide association studies (TWAS), gene expression values are predicted using genotype data and tested for association with a phenotype. The power of this approach to detect associations relies, at least in part, on the… read more here.
Keywords: accuracy; tissue; association; prediction accuracy ... See more keywords
Prediction accuracy of pXRF, MIR, and Vis‐NIR spectra for soil properties—A review
Sign Up to like & getrecommendations! Published in 2025 at "Soil Science Society of America Journal"
DOI: 10.1002/saj2.70028
Abstract: Here, we review the prediction accuracy for soil properties using portable X‐ray fluorescence (pXRF), mid‐infrared (MIR), and visible near‐infrared (Vis‐NIR) and the factors impacting predictions and its accuracy. In total, 305 published papers were reviewed,… read more here.
Keywords: prediction accuracy; prediction; soil; vis nir ... See more keywords
The Limitations of Existing Approaches in Improving MicroRNA Target Prediction Accuracy.
Sign Up to like & getrecommendations! Published in 2017 at "Methods in molecular biology"
DOI: 10.1007/978-1-4939-7046-9_10
Abstract: MicroRNAs (miRNAs) are small (18-24 nt) endogenous RNAs found across diverse phyla involved in posttranscriptional regulation, primarily downregulation of mRNAs. Experimentally determining miRNA-mRNA interactions can be expensive and time-consuming, making the accurate computational prediction of… read more here.
Keywords: mirna mrna; target; prediction accuracy; limitations existing ... See more keywords
A Machine Learning-Based Method to Identify Bipolar Disorder Patients
Sign Up to like & getrecommendations! Published in 2022 at "Circuits, Systems, and Signal Processing"
DOI: 10.1007/s00034-021-01889-1
Abstract: Bipolar disorder is a serious psychiatric disorder characterized by periodic episodes of manic and depressive symptomatology. Due to the high percentage of people suffering from severe bipolar and depressive disorders, the modelling, characterisation, classification and… read more here.
Keywords: prediction accuracy; disorder; method; machine learning ... See more keywords
Gramian matrix data collection-based random forest classification for predictive analytics with big data
Sign Up to like & getrecommendations! Published in 2019 at "Soft Computing"
DOI: 10.1007/s00500-019-04014-2
Abstract: Prediction is the process of analyzing the current and past events to identify future events. The prediction of the subsequent future conditions is still a revealing stage in many applications to minimize the risk level.… read more here.
Keywords: prediction accuracy; collection based; data collection; prediction ... See more keywords
Energy demand forecasting using a novel remnant GM(1,1) model
Sign Up to like & getrecommendations! Published in 2020 at "Soft Computing"
DOI: 10.1007/s00500-020-04765-3
Abstract: Grey prediction models play a significant role in forecasting energy demand, particularly the GM(1,1) model. To increase the prediction accuracy of the original GM(1,1) model, the corresponding residual GM(1,1) model is often recommended. However, the… read more here.
Keywords: model; prediction accuracy; prediction; energy demand ... See more keywords
The power load’s signal analysis and short-term prediction based on wavelet decomposition
Sign Up to like & getrecommendations! Published in 2017 at "Cluster Computing"
DOI: 10.1007/s10586-017-1316-3
Abstract: The complex signal represented by power load is affected by many factors, so the signal components are very complicated. So that, it is difficult to obtain satisfactory prediction accuracy by using a single model for… read more here.
Keywords: model; prediction accuracy; prediction; power load ... See more keywords
Impact of the complexity of genotype by environment and dominance modeling on the predictive accuracy of maize hybrids in multi-environment prediction models
Sign Up to like & getrecommendations! Published in 2021 at "Euphytica"
DOI: 10.1007/s10681-021-02779-y
Abstract: The prediction accuracy of multi-environment prediction models can be affected by the complexity of the genotype by environment interaction (G×E). Moreover, depending on the trait genetic architecture, accounting for non-additive effects, such as dominance effects,… read more here.
Keywords: multi environment; prediction accuracy; prediction; complexity ... See more keywords
Improvement of prediction accuracy by choosing resampling distribution via cross-validation
Sign Up to like & getrecommendations! Published in 2024 at "Behaviormetrika"
DOI: 10.1007/s41237-024-00239-0
Abstract: In a regression model, prediction is typically performed after model selection. The large variability in the model selection makes the prediction unstable. Thus, it is essential to reduce the variability in model selection and improve… read more here.
Keywords: prediction accuracy; resampling distribution; distribution; prediction ... See more keywords
Gaussian Processes for improving orbit prediction accuracy
Sign Up to like & getrecommendations! Published in 2019 at "Acta Astronautica"
DOI: 10.1016/j.actaastro.2019.05.014
Abstract: Abstract A machine learning (ML) approach has been recently proposed to improve the orbit prediction accuracy of resident space objects (RSOs) through learning from historical data. Previous results have shown that the ML approach can… read more here.
Keywords: orbit prediction; gaussian processes; prediction accuracy;
Study on influencing factors of prediction accuracy of support vector machine (SVM) model for NOx emission of a hydrogen enriched compressed natural gas engine
Sign Up to like & getrecommendations! Published in 2018 at "Fuel"
DOI: 10.1016/j.fuel.2018.07.009
Abstract: Abstract In recent years, support vector machine (SVM) method has been rapidly developed because of its great advantage in solving small sample regression problems. Based on the prediction accuracy of NO x emission, the SVM… read more here.
Keywords: svm; regression; model; prediction accuracy ... See more keywords