The flowchart showing the optimization process of the hybrid methods using BEOSA as the base algorithm and SA and FFA as integrated algorithms. by Olaide N. Oyelade (14047002)

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An illustrated example of Algorithm 1 (Fig 1). by Kathleen M. Jagodnik (10170617)

The developed algorithm to calculate Gene-Disease Prioritization Score (GDPS). by Kathleen M. Jagodnik (10170617)

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)

Dataset description. by Rajan Vohra (10689820)

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Prevalence of normocytic, microcytic and macrocytic by age. by Rajan Vohra (10689820)

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Summary of the results obtained using the dataset3 (SMOTE). by Rajan Vohra (10689820)

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Prevalence of mild, moderate and severe anemia in percentage by age. by Rajan Vohra (10689820)

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Gender wise prevalence of Anemia in the study population. by Rajan Vohra (10689820)

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Summary of the results obtained using the dataset4 (SMOTE and feature selected). by Rajan Vohra (10689820)

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Prevalence of mild, moderate and severe anemia by age. by Rajan Vohra (10689820)

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Prevalence of mild, moderate and severe anemia by age. by Rajan Vohra (10689820)

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Summary of the results obtained using the dataset2 (feature selected). by Rajan Vohra (10689820)

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Framework of the proposed model. by Rajan Vohra (10689820)

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Summary of the results obtained using the dataset1 (Anemia original dataset). by Rajan Vohra (10689820)

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Prevalence of normocytic, microcytic and macrocytic by age. by Rajan Vohra (10689820)

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Feature selection. by Rajan Vohra (10689820)

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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. …”

Comparison of key techniques in their literature. 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. …”

Ensemble model architecture. 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. …”