Logistic Classification Model of the Effort Expectancy. by Anis Ben Ghorbal (22521828)

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Kernel Density Plot of Effort Expectancy Scores. by Anis Ben Ghorbal (22521828)

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Characteristics of Participant by the ease of using the telehealth system “Effort Expectancy”. by Anis Ben Ghorbal (22521828)

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Frequency and Density plot of features Across Classes of Ease of using the telehealth system “Effort Expectancy”. by Anis Ben Ghorbal (22521828)

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Simulation results for the expected values. by Jürgen Kampf (21354027)

“…Among the remaining algorithms, in most situations we tested, predictive mean matching performed best.…”

ROC Curve and Classification Thresholds [33–36]. by Anis Ben Ghorbal (22521828)

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Classification of smart city application projects. by Gongyi Jiang (20896467)

Result of the classification. by Subin Ham (19704398)

“…The classification approach proposed in this study is expected to encourage the rapid and accurate classification of various lot shapes.…”

Telehealth. by Anis Ben Ghorbal (22521828)

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Characteristics of Highly Agreed Participants among Disability Subgroups, Odds Ratio (OR), and 95% Confidence Interval (CI). by Anis Ben Ghorbal (22521828)

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Information Value Scores (Binary Logistic Regression) and Feature Importance Scores (Random Forest) Across Features (for IVs from LR, a bar with dashed border indicates a significa... by Anis Ben Ghorbal (22521828)

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Random Forest Framework. by Anis Ben Ghorbal (22521828)

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Accuracy Results from Random Forest and Binary Logistic Regression Models by Data Types. by Anis Ben Ghorbal (22521828)

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Algorithm stages for the clustering phase. by Julien Roche (611898)

“…The method relies on starting the clustering algorithm with an initial higher number of groups than expected from the ploidy level of the samples, followed by merging groups that are too close to each other to be considered as distinct genotypes. …”

Confusion matrix when inferring the mode of selection. by Adam G. Fine (21763286)

Dataset configuration. by Subin Ham (19704398)

“…The classification approach proposed in this study is expected to encourage the rapid and accurate classification of various lot shapes.…”

Projected LULC of BMNP (2033 and 2053). by Firdissa Sadeta Tiye (21222102)

“…The Random Forest (RF) classification algorithm was used for image classification, while the Cellular Automata Artificial Neural Networks (CA-ANN) model within the Modules for Land Use Change Simulations (MOLUSCE) plugin of QGIS was employed for future LULC projection. …”

Definition of LULC classes. by Firdissa Sadeta Tiye (21222102)

“…The Random Forest (RF) classification algorithm was used for image classification, while the Cellular Automata Artificial Neural Networks (CA-ANN) model within the Modules for Land Use Change Simulations (MOLUSCE) plugin of QGIS was employed for future LULC projection. …”

Data types and their sources. by Firdissa Sadeta Tiye (21222102)

“…The Random Forest (RF) classification algorithm was used for image classification, while the Cellular Automata Artificial Neural Networks (CA-ANN) model within the Modules for Land Use Change Simulations (MOLUSCE) plugin of QGIS was employed for future LULC projection. …”

Location map of the study area. by Firdissa Sadeta Tiye (21222102)

“…The Random Forest (RF) classification algorithm was used for image classification, while the Cellular Automata Artificial Neural Networks (CA-ANN) model within the Modules for Land Use Change Simulations (MOLUSCE) plugin of QGIS was employed for future LULC projection. …”