Searched for: subject%3A%22k%255C-nearest%255C+neighbors%22
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document
Baez Lozada, Luis Carlos (author)
This research evaluates the applicability of Multivariate Imputation by Chained Equations (MICE) for estimating missing well-log data across different sedimentary basis. Utilizing various machine learning techniques including XGBoost (XGB), Random Forest (RF), K-Nearest Neighbors (KNR), and Bayesian Ridge (BR), the performance of MICE was tested...
master thesis 2023
document
Liu, Minne (author), Ibrahim, Mesfin S. (author), Wen, Minzhen (author), Li, Sheng (author), Wang, An (author), Zhang, Kouchi (author), Fan, J. (author)
Spectral power distribution (SPD) is the radiation power intensity at different wavelengths, containing the most basic photometric and colorimetric performance of the illuminant, which is able to predict the lifetime of LEDs. This paper proposes an SPD model assisted by machine learning algorithms to detect the early failure of white LEDs. The...
conference paper 2023
document
Han, Budi (author)
Personality disorders affect 1 in 7 adults reducing their quality of life. Schema-focused therapy (SFT) has become very popular in Psychotherapy in the treatment of personality disorders (PD), unfortunately there is still in increasing societal need for such mental healthcare. Automation in the assessment of SFT allows for Ecological Momentary...
bachelor thesis 2021
document
Man, K.W. (author)
As software is produced more and more every year, software also gets exploited more. This exploitation can lead to huge monetary losses and other damages to companies and users. The exploitation can be reduced by automatically detecting the software vulnerabilities that leads to exploitation. Unfortunately, the state-of-the-art methods for this...
master thesis 2020
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Nasiri, Jalal A. (author), Mir, S.A.M. (author)
Among the extensions of twin support vector machine (TSVM), some scholars have utilized K-nearest neighbor (KNN) graph to enhance TSVM’s classification accuracy. However, these KNN-based TSVM classifiers have two major issues such as high computational cost and overfitting. In order to address these issues, this paper presents an enhanced...
journal article 2020
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Dai, Yinghao (author)
Precipitation has high spatial and temporal uncertainty, which makes it challenging to predict. We focus specifically on extreme amounts of precipitation. The Royal Dutch Meteorological Institute (KNMI) uses a numerical model, approximating the solutions to partial differential equations, to forecast precipitation and other metrics about the...
bachelor thesis 2018
document
Akbari, M. (author), Van Overloop, P.J.A.T.M. (author), Afshar, A. (author)
Instance based learning (IBL) algorithms are a common choice among data driven algorithms for inflow forecasting. They are based on the similarity principle and prediction is made by the finite number of similar neighbors. In this sense, the similarity of a query instance is estimated according to the closeness of its feature vector with those...
journal article 2010
Searched for: subject%3A%22k%255C-nearest%255C+neighbors%22
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