The proposed method uses Quality of Service (QoS) attributes from a side, and reputation values of similar services from the second side, to estimate the reputation values of newcomer services. Basically, it employs regression models, including Support Vector Regression, in the estimation process of...
FAIREDU: A Multiple Regression-Based Method for Enhancing Fairness in Machine Learning Models for Educational Applications Fairness in artificial intelligence and machine learning (AI/ML) models is becoming critically important, especially as decisions made by these systems imp... N Pham,MK Do,TV Dai...
We use the lasso as a regression method with subset selection (for both the ‘average’ and the ‘smoothing’ type); the predictors are selected by including anℓ1penalty on the vector of regression weights during the loss minimization, which effectively sets many of the weights to zero54. ...
are not included in this classification, e.g., frequent graph mining methods [33,34], approaches for mining frequent tree-like patterns [35], mining frequent movement patterns for a mobile user [36], and mining web usage data [37], because they are not related to the proposed method. A...
Genomic control (GC) method is a useful tool to correct for the cryptic relatedness in population-based association studies. It was originally proposed for correcting for the variance inflation of Cochran-Armitage's additive trend test by using informati
The RSM is a method for analyzing the results of experiments. Calculating the R2, R2 adjusted, and R2 predicted quantity determined the model’s significance level. The calculated F-quantity is used to determine the influence of the factors on the measured results. The greater the F-quantity ...
For each search point, the Random Search (Robust) method builds a model using 10 different random seeds, picks the set of hyperparameter values with the median model performance, then moves to the next search point. The tool repeats this process until it searches all candidate search points. ...
It also uses the proportional selection method to increase accuracy and reduce training time for SVR. Some evaluations are conducted to validate the feasibility of the two regression-based service availability prediction schemes for the Ubike system. 展开 ...
Extreme learning machines for regression based on V-matrix method Article 10 June 2017 Training an extreme learning machine by localized generalization error model Article 17 January 2018 Change history 18 January 2023 Author biography details has been updated. Abbreviations ELM: Extreme learning ...
The greater discrimination between states afforded using logistic regression as opposed to the previous Gaussian distribution-based emission probability estimation as well as the use of an extended Viterbi algorithm allows this method to significantly outperform the current state-of-the-art method based ...