ROC analysis of the Machine Learning Algorithm. by Stephan Ellmann (314565)

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WGCNA and machine learning algorithms. by Shushu Wang (6870191)

Functions of a translation model. by Beibei Ren (9662634)

Table_1_Functional Outcome Prediction in Ischemic Stroke: A Comparison of Machine Learning Algorithms and Regression Models.DOCX by Shakiru A. Alaka (9302864)

“…We evaluate the predictive accuracy of machine-learning algorithms for predicting functional outcomes in acute ischemic stroke patients after endovascular treatment.…”

Rule-in and rule-out criteria provided by the machine learning algorithm. by Stephan Ellmann (314565)

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Great machine learning performance with multiple classification algorithms. by Sydney C. Weiser (15383531)

Data_Sheet_1_Functional Outcome Prediction in Ischemic Stroke: A Comparison of Machine Learning Algorithms and Regression Models.PDF by Shakiru A. Alaka (9302864)

“…We evaluate the predictive accuracy of machine-learning algorithms for predicting functional outcomes in acute ischemic stroke patients after endovascular treatment.…”

Dataset for 'An Automated Workflow of Deep Learning Ensemble Model with Principal Component Analysis for Enhanced Material Characterisation in Energy Dispersive Spectroscopy' by Fanzhi Su (21005174)

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Key gene identification based on two machine learning algorithms. by Lijun Guo (605276)

Algorithm process of BPNN. by Xiaoxiang Cao (12644851)

Parameters of the test function. by Yiqiong Gao (16698968)

“…A Gaussian mutation strategy was integrated with IFPA to optimise the initial input weights and thresholds of the extreme learning machine (ELM), improve the balance and exploration ability of the algorithm, and increase the efficiency and accuracy for identifying pipeline defects. …”

Model construction and validation (A) Construction of the model based on multiple machine learning algorithms. by Chengting Wu (21485612)

Machine learning algorithm parameters. by Namal Rathnayake (15361124)

“…Results of the study showcased that both systems can simulate river flows as a function of catchment rainfalls; however, the Cat gradient Boosting algorithm (CatBoost) has a computational edge over the Adaptive Network Based Fuzzy Inference System (ANFIS). …”

Construction of the PRG score index using integrated machine learning algorithms. by Xiangxin Wu (22320058)

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Unimodal benchmark functions. by Rahila Hafiz (18137254)

“…We propose a fusion of this algorithm with a discrete recombinant evolutionary strategy to enhance initialization diversity. …”

Multimodal benchmark functions. by Rahila Hafiz (18137254)

“…We propose a fusion of this algorithm with a discrete recombinant evolutionary strategy to enhance initialization diversity. …”

Pipeline of the interactor algorithm. by Jose Cleydson F. Silva (8685594)

An Efficient Algorithm for Minimizing Multi Non-Smooth Component Functions by Minh Pham (2458399)

“…<p>Many problems in statistics and machine learning can be formulated as an optimization problem of a finite sum of nonsmooth convex functions. …”

Automated diagnosis of heart valve degradation using novelty detection algorithms and machine learning by Bernhard Vennemann (7434353)

“…Blood flow recordings from a flow meter at the location of the ascending aorta were analyzed with the algorithms introduced in this article and a diagnostic index was defined that reflects the severity of valvular degradation. …”

The Effect of Machine Learning Algorithms on the Prediction of Layer-by-Layer Coating Properties by Tijana Šušteršič (14519970)

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