Spatial variables selected for LULC modeling. حسب 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. …"

Area of LULC changes in BMNP (1993 – 2023). حسب 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. …"

A reas of actual and simulated LULC in 2023. حسب 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. …"

BPNN structure. حسب Gongyi Jiang (20896467)

"…The research results indicate that: (1) the training results and expected values of the ten cities are relatively consistent, and the classification of rural revitalization development is good; (2) The five major indicators of tourism information services, tourism security services, tourism transportation services, tourism environment services, and tourism management services all meet the consistency test, and the consistency test results are all less than 0.1, confirming the reliability and effectiveness of the research data; (3) The tourism information and management services are mainly evaluated at level C, accounting for 62% and 62.5% respectively. …"

T-test results. حسب Gongyi Jiang (20896467)

"…The research results indicate that: (1) the training results and expected values of the ten cities are relatively consistent, and the classification of rural revitalization development is good; (2) The five major indicators of tourism information services, tourism security services, tourism transportation services, tourism environment services, and tourism management services all meet the consistency test, and the consistency test results are all less than 0.1, confirming the reliability and effectiveness of the research data; (3) The tourism information and management services are mainly evaluated at level C, accounting for 62% and 62.5% respectively. …"

Setting of specific indexes. حسب Gongyi Jiang (20896467)

"…The research results indicate that: (1) the training results and expected values of the ten cities are relatively consistent, and the classification of rural revitalization development is good; (2) The five major indicators of tourism information services, tourism security services, tourism transportation services, tourism environment services, and tourism management services all meet the consistency test, and the consistency test results are all less than 0.1, confirming the reliability and effectiveness of the research data; (3) The tourism information and management services are mainly evaluated at level C, accounting for 62% and 62.5% respectively. …"

The four areas of interest to the patients. حسب Anne Lübbeke (3918686)

"…</p><p>Methods</p><p>We created the information tool “Patients like me” in four steps. (1) The knowledge basis was the systematically collected detailed exposure and outcome information from the Geneva Arthroplasty Registry established 1996. (2) From the registry we randomly selected 275 patients about to undergo or having already undergone THA and asked them via interviews and a survey which benefits and harms associated with the operation and daily life with the prosthesis they perceived as most important. (3) The identified relevant data (39 predictor candidates, 15 outcomes) were evaluated using Conditional Inference Trees analysis to construct a classification algorithm for each of the 15 outcomes at three different time points/periods. …"

An example of a complication. حسب Anne Lübbeke (3918686)

"…</p><p>Methods</p><p>We created the information tool “Patients like me” in four steps. (1) The knowledge basis was the systematically collected detailed exposure and outcome information from the Geneva Arthroplasty Registry established 1996. (2) From the registry we randomly selected 275 patients about to undergo or having already undergone THA and asked them via interviews and a survey which benefits and harms associated with the operation and daily life with the prosthesis they perceived as most important. (3) The identified relevant data (39 predictor candidates, 15 outcomes) were evaluated using Conditional Inference Trees analysis to construct a classification algorithm for each of the 15 outcomes at three different time points/periods. …"

Baseline characteristics. حسب Anne Lübbeke (3918686)

"…</p><p>Methods</p><p>We created the information tool “Patients like me” in four steps. (1) The knowledge basis was the systematically collected detailed exposure and outcome information from the Geneva Arthroplasty Registry established 1996. (2) From the registry we randomly selected 275 patients about to undergo or having already undergone THA and asked them via interviews and a survey which benefits and harms associated with the operation and daily life with the prosthesis they perceived as most important. (3) The identified relevant data (39 predictor candidates, 15 outcomes) were evaluated using Conditional Inference Trees analysis to construct a classification algorithm for each of the 15 outcomes at three different time points/periods. …"

Building blocks of the project. حسب Anne Lübbeke (3918686)

"…</p><p>Methods</p><p>We created the information tool “Patients like me” in four steps. (1) The knowledge basis was the systematically collected detailed exposure and outcome information from the Geneva Arthroplasty Registry established 1996. (2) From the registry we randomly selected 275 patients about to undergo or having already undergone THA and asked them via interviews and a survey which benefits and harms associated with the operation and daily life with the prosthesis they perceived as most important. (3) The identified relevant data (39 predictor candidates, 15 outcomes) were evaluated using Conditional Inference Trees analysis to construct a classification algorithm for each of the 15 outcomes at three different time points/periods. …"

Safe Policy Learning through Extrapolation: Application to Pre-trial Risk Assessment حسب Eli Ben-Michael (10803815)

"…We examine a particular case of algorithmic pre-trial risk assessments in the US criminal justice system, which provide deterministic classification scores and recommendations to help judges make release decisions. …"

Statistics of the different columns. حسب Jürgen Kampf (21354027)

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

Simulation results for the variances. حسب Jürgen Kampf (21354027)

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

Test MCAR vs. MAR. حسب Jürgen Kampf (21354027)

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

Simulation results for Cox regression models. حسب Jürgen Kampf (21354027)

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

Simulation results for linear regression models. حسب Jürgen Kampf (21354027)

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

Overall flowchart of the proposed model. حسب Cai Yuanqing (22513351)

"…This paper presents a method for credit risk prediction for listed companies that uses an off-policy proximal policy optimization (PPO) algorithm for feature selection and imbalanced classification. …"

Table 1_A random forest dynamic threshold imputation method for handling missing data in cognitive diagnosis assessments.pdf حسب Xiaofeng You (21987266)

"…A simulation study showed that the classification of attribute profiles when using RFDTI to impute missing data was always better than the four commonly used traditional methods (i.e., person mean imputation, two-way imputation, expectation–maximization algorithm, and multiple imputation). …"

Unsupervised machine learning with different sampling strategies and topographic factors for distinguishing between landslide source and runout areas to improve landslide inventory... حسب Jhe-Syuan Lai (19733974)

"…Three unsupervised machine learning algorithms were employed to distinguish between the features of landslide sources and runout areas for Typhoon Morakot. …"

Table 1_Non-obtrusive monitoring of obstructive sleep apnea syndrome based on ballistocardiography: a preliminary study.docx حسب Biyong Zhang (20906192)

"…Furthermore, our approach directly extracts features from BCG signals without employing a complex algorithm to derive respiratory and heart rate signals as often done in literature, further simplifying the algorithm pipeline. …"