Results of Decision tree. by Balraj Preet Kaur (20370832)

“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”

Adaboost classifier results. by Balraj Preet Kaur (20370832)

“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”

Results of Lightbgm. by Balraj Preet Kaur (20370832)

“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”

Results of Lightbgm. by Balraj Preet Kaur (20370832)

“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”

Feature selection process. by Balraj Preet Kaur (20370832)

“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”

Results of KNN. by Balraj Preet Kaur (20370832)

“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”

After upsampling. by Balraj Preet Kaur (20370832)

“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”

Results of Extra tree. by Balraj Preet Kaur (20370832)

“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”

Gradient boosting classifier results. by Balraj Preet Kaur (20370832)

“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”

Microsoft excel file containing exhaustive list of Abbreviated-Injury Scale codes used to generate binary variables encoding the presence or absence of injury to various body regio... by Michael D. Cobler-Lichter (22492930)

Classification baseline performance. by Doaa Sami Khafaga (21463870)

“…The contributions include developing a baseline Convolutional Neural Network (CNN) that achieves an initial accuracy of 86.29%, surpassing existing state-of-the-art deep learning models. Further integrate the binary variant of OcOA (bOcOA) for effective feature selection, which reduces the average classification error to 0.4237 and increases CNN accuracy to 93.48%. …”

Feature selection results. by Doaa Sami Khafaga (21463870)

“…The contributions include developing a baseline Convolutional Neural Network (CNN) that achieves an initial accuracy of 86.29%, surpassing existing state-of-the-art deep learning models. Further integrate the binary variant of OcOA (bOcOA) for effective feature selection, which reduces the average classification error to 0.4237 and increases CNN accuracy to 93.48%. …”

ANOVA test result. by Doaa Sami Khafaga (21463870)

“…The contributions include developing a baseline Convolutional Neural Network (CNN) that achieves an initial accuracy of 86.29%, surpassing existing state-of-the-art deep learning models. Further integrate the binary variant of OcOA (bOcOA) for effective feature selection, which reduces the average classification error to 0.4237 and increases CNN accuracy to 93.48%. …”

Summary of literature review. by Doaa Sami Khafaga (21463870)

“…The contributions include developing a baseline Convolutional Neural Network (CNN) that achieves an initial accuracy of 86.29%, surpassing existing state-of-the-art deep learning models. Further integrate the binary variant of OcOA (bOcOA) for effective feature selection, which reduces the average classification error to 0.4237 and increases CNN accuracy to 93.48%. …”

Design and implementation of the Multiple Criteria Decision Making (MCDM) algorithm for predicting the severity of COVID-19. by Jiaqing Luo (10975030)

Hierarchical clustering to infer a binary tree with <i>K</i> = 4 sampled populations. by Tristan Mary-Huard (3864)

“…After <i>K</i> − 2 = 2 steps, the resulting tree is binary and the algorithm stops.</p>…”

Probability graphical model of scMSI. by Yuqian Liu (1413763)

Testing algorithm for modified 2-tiered approaches to Lyme disease diagnosis. by Richard Porwancher (11413931)

The workflow diagram for the gene expression biomarker study which involve using principal component analysis (PCA) to reduce the number of features (principal components), thus re... by Aninda Astuti (21736334)

Model performance and benchmarking for multiclass MOA and 30S/50S protein-synthesis classifiers. by Josh L. Espinoza (10492448)