Optimization process of BO algorithm. حسب Hoa Thi Trinh (20347834)

"…The results show that Gaussian Process emerged as the most efficient solution compared to other optimization algorithms, providing the lowest Mean Square Error and achieving a prediction R² of 0.998 for the training set, 0.972 for the validation set and 0.984 for the test set, while BO—Random Forest and Random Search performed as well on the training and test sets as Gaussian Process but significantly worse on the validation set, specifically R² on the validation set of BO—Random Forest and Random Search were 0.970 and 0.969 respectively over the entire dataset including all cross-sectional shapes of the RC wall. …"

A framework for improving localisation prediction algorithms. حسب Sven B. Gould (12237287)

"…Proteins with non-canonical internal motifs, or those dually targeted need to be taken into account (as they help to better distinguish between pNTS and mNTS features) and validated data could be sorted according to whether it is part of a core- or pan-proteome. Classifiers on which the algorithms are trained could include parameters such as the evolutionary distance of a species, non-coding regions, or a protein’s abundance as a currently neglected factor. …"

Algorithm process. حسب Wei Cui (92129)

Visualization process of AOSD algorithm. حسب Lu Liu (171341)

Performance of algorithms outside the training species. حسب Sven B. Gould (12237287)

"…<p>Comparison of predicted versus experimentally localised plastid <b>(a)</b> and mitochondrial <b>(b)</b> proteome numbers. …"

Processing pipeline dependency chain. حسب Michael E. Kim (21956727)

Feature importance, contribution and dependency analysis. حسب Chao Wang (146527)

Dataset for Fine-Tuning Code Generation Models: Kannada-English Algorithmic Statements and Python Code حسب Goutami Sooda (20714729)

The genome coding scheme. حسب Wenbing Shi (5806160)

الموضوعات:

(a) Prediction using traditional algorithm. (b) Prediction using optimization algorithm. حسب Dandan Wang (286632)

"…<p>(a) Prediction using traditional algorithm. (b) Prediction using optimization algorithm.…"

Data and code resources. حسب Sam Hall-McMaster (10343795)

Source Code and Dataset حسب Swathi Ganesan (14394924)

Prediction results of individual models. حسب Ahmed M. Elshewey (21463867)

"…The capacity to confront and overcome this obstacle is where machine learning and metaheuristic algorithms shine. This study introduces the Adaptive Dynamic Particle Swarm Optimization enhanced with the Guided Whale Optimization Algorithm (AD-PSO-Guided WOA) for rainfall prediction. …"

The interleaved processes. حسب Dawei Wang (471687)

The process of IHWGWO. حسب Dawei Wang (471687)

GA pseudo-code. حسب Jianpeng Zhang (528185)

"…The introduction of gated recurrent unit addresses the dependency of time series data and effectively solves the problem of gradient vanishing or exploding in traditional recurrent neural networks when processing long sequence data. …"

Overall process planning. حسب Dawei Wang (471687)

Pseudocode for the missForestPredict algorithm. حسب Elena Albu (15181070)

"…Missing data in input variables often occur at model development and at prediction time. The missForestPredict R package proposes an adaptation of the missForest imputation algorithm that is fast, user-friendly and tailored for prediction settings. …"

Workflow of our study to evaluate the performance of GNNs compared to benchmark algorithms. حسب Daniel Walke (21680915)

Data Sheet 1_Development of machine learning algorithms to predict viral load suppression among HIV patients in Conakry (Guinea).docx حسب Degninou Yehadji (3451511)