Geometric interpretation and data visualisation equivalent describing the DI algorithmic pipeline. by Borjan Milinkovic (21349908)

Summary of the feature selection algorithms. by Martin Kostadinov (20410120)

Cost of implementing different screening algorithm. by Tushar Garg (9283574)

Choices on individual test tasks were not explained by model-free perseveration. by Sam Hall-McMaster (10343795)

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Cost functions implemented in Neuroptimus. by Máté Mohácsi (20469514)

“…<div><p>Finding optimal parameters for detailed neuronal models is a ubiquitous challenge in neuroscientific research. …”

MEA-BP neural network algorithm flowchart. by Dongling Ma (1269888)

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

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Experimental design. by Sam Hall-McMaster (10343795)

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Behavioral results. by Sam Hall-McMaster (10343795)

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Choice behavior on individual test tasks. by Sam Hall-McMaster (10343795)

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Data and Scripts for 'A Predictive Model for Attention-deficit/hyperactivity Disorder and Its Subtypes in Children: A Back-propagation Neural Network Optimized with Genetic Algorithms Based on Multidimensional Cognitive Ability Tests' by Wang (20310746)

“…Using <a href="" target="_blank">multidimensional cognitive ability tests</a> and a <a href="" target="_blank">back-propagation neural network</a> optimized by a genetic algorithm, this study developed a computer-aided diagnostic model to distinguish children with attention-deficit/hyperactivity disorder and its specific subtypes. …”

The block diagram of the ASO algorithm implementation for inverse modeling. by Ahmad Al-Talabi (21387479)

NAR dynamic neural network model. by Zhanni Huang (20577481)

“…Therefore, this article uses the random forest model and XGBoost algorithm to identify core price indicators, and uses an innovative rolling NAR dynamic neural network model to simulate and predict second-hand sailboat price data. …”

Supervised Predictive Modeling of High-dimensional Data with Group l0-norm Constrained Neural Networks by Zhihuang Yang (22530437)

“…By leveraging group <math><mrow><msub><mrow><mi>l</mi></mrow><mn>0</mn></msub></mrow></math>-norm constrained neural networks, the proposed approach aims to simultaneously extract crucial features and estimate the underlying model function with statistically guaranteed accuracy. …”

Licking behaviors and neural firings of the model. by Huu Hoang (9188747)

Subjects: “…supervised learning algorithms…”

The diagram of the LSTM neural network. by Mohd Sakib (20565228)

Data and Scripts for 'Application of Multidimensional Cognitive Ability Tests in Computer-Assisted Diagnosis of Attention-Deficit/Hyperactivity Disorder and Its Subtypes in Children: Based on A Genetic Algorithm Optimized Back-Propagation Neural Network Predictive Model' by Wang (20310746)

“…Using <a href="" target="_blank">multidimensional cognitive ability tests</a> and a <a href="" target="_blank">back-propagation neural network</a> optimized by a genetic algorithm, this study developed a computer-aided diagnostic model to distinguish children with attention-deficit/hyperactivity disorder and its specific subtypes. …”

Neural Network Structure Parameters. by Yu Jie Guang (22184340)

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Flowchart of GA-PSO-BP neural network model. by Jining Wang (3369305)

“…To address this issue, the research employs a genetic-particle swarm optimization (GA-PSO) algorithm and develops a GA-PSO-BP neural network model through the integration of the BP neural network. …”

RF Algorithm error rate of the model. by Halit Tutar (20678455)

“…For this purpose, Artificial Neural Networks (ANN), Automatic Linear Model (ALM), Random Forest (RF) Algorithm and Multivariate Adaptive Regression Spline (MARS) Algorithm were used, and the prediction performances of these methods were compared. …”