Results 41 to 50 of about 197,316 (278)

Predicting time to graduation at a large enrollment American university

, 2020
The time it takes a student to graduate with a university degree is mitigated by a variety of factors such as their background, the academic performance at university, and their integration into the social communities of the university they attend ...
Aiken, John M., Caballero, Marcos D., De Bin, Riccardo, Hjorth-Jensen, Morten   +3 more
core   +1 more source

Distributional Gradient Boosting Machines

, 2022
Distributional Regression, LightGBM, Normalizing Flow, Probabilistic Forecasting ...
März, Alexander, Kneib, Thomas
openaire   +2 more sources

Predicting the Future Burden of Renal Replacement Therapy in Türkiye Using National Registry Data and Comparative Modeling Approaches

Therapeutic Apheresis and Dialysis, EarlyView.
ABSTRACT Background Chronic kidney disease is a growing public health problem worldwide, and the number of patients requiring renal replacement therapy is steadily increasing. Türkiye has experienced a similar rise in both the incidence and prevalence of renal replacement therapy over the past decades; however, national‐level projections of future ...
Arzu Akgül, Neriman Sıla Koç, Berrak Itır Aylı   +2 more
wiley   +1 more source

Sequential Training of Neural Networks With Gradient Boosting

IEEE Access, 2023
This paper presents a novel technique based on gradient boosting to train the final layers of a neural network (NN). Gradient boosting is an additive expansion algorithm in which a series of models are trained sequentially to approximate a given function.
Seyedsaman Emami, Gonzalo Martinez-Munoz
doaj   +1 more source

GEFCOM 2014 - Probabilistic Electricity Price Forecasting

, 2015
Energy price forecasting is a relevant yet hard task in the field of multi-step time series forecasting. In this paper we compare a well-known and established method, ARMA with exogenous variables with a relatively new technique Gradient Boosting ...
Barta, Gergo, Borbely, Gyula, Henk, Tamas, Kazi, Sandor, Nagy, Gabor   +4 more
core   +1 more source

RaMBat: Accurate identification of medulloblastoma subtypes from diverse data sources with severe batch effects

Molecular Oncology, EarlyView.
To integrate multiple transcriptomics data with severe batch effects for identifying MB subtypes, we developed a novel and accurate computational method named RaMBat, which leveraged subtype‐specific gene expression ranking information instead of absolute gene expression levels to address batch effects of diverse data sources.
Mengtao Sun, Jieqiong Wang, Shibiao Wan
wiley   +1 more source

AI meets economics: Can deep learning surpass machine learning and traditional statistical models in inflation time series forecasting?

Data Science in Finance and Economics
This study examined the forecasting ability of deep learning (DL) and machine learning (ML) models against benchmark traditional statistical models for the monthly inflation rates in the USA. The study compared various DL and ML models like transformers,
Ezekiel NN Nortey, Edmund F. Agyemang, Enoch Sakyi-Yeboah, Obu-Amoah Ampomah, Louis Agyekum   +4 more
doaj   +1 more source

Compact Multi-Class Boosted Trees

, 2017
Gradient boosted decision trees are a popular machine learning technique, in part because of their ability to give good accuracy with small models. We describe two extensions to the standard tree boosting algorithm designed to increase this advantage ...
Colthurst, Thomas, Haykal, Salem, Hendry, Gilbert, Ponomareva, Natalia, Radpour, Soroush   +4 more
core   +1 more source

Gradient-boosted equivalent sources

Geophysical Journal International, 2021
SUMMARY The equivalent source technique is a powerful and widely used method for processing gravity and magnetic data. Nevertheless, its major drawback is the large computational cost in terms of processing time and computer memory. We present two techniques for reducing the computational cost of equivalent source processing: block ...
Santiago R. Soler, Leonardo Uieda
openaire   +3 more sources

Engineering tandem VHHs to target different epitopes to enhance antibody‐dependent cell‐mediated cytotoxicity

FEBS Open Bio, EarlyView.
Tandem VHH targeting distinct EGFR epitopes were engineered into a monovalent bispecific antibody (7D12‐EGA1‐Fc) with more potent ADCC without increasing affinity to EGFR. Structural modeling of 7D12‐EGA1‐Fc showed cross‐linking of separate EGFR domains to enhance CD16a engagement on NK cells.
Yuqiang Xu, Hao Jiang, Limin Chen, Fulai Zhou, Ying Jin, Mark L. Chiu   +5 more
wiley   +1 more source