Q-Learning state definition based on objective medians. by Zhongfeng Li (3965060)

Subjects:

Recommendations on device selection and programming. by Pascal Defaye (22331815)

Extraction of the number of impactful features using sequential forward selection. by M. A. Habib (16839161)

Consensus and single-method networks inferred on the liver cirrhosis dataset, followed by CORE-clustering algorithm to identify the microbial guilds. by Camille Champion (15238934)

Algorithm for MFISTA-VA [30]. by Faisal Najeeb (20542714)

“…GRASP uses Temporal Total Variation (TV) norm as a sparsity transform to promote sparsity among multi-coil MRI data and Nonlinear Conjugate Gradient (NL-CG) algorithm to obtain an optimal solution. Additionally, GRASP uses NUFFT gridding to map Golden-angle-radial data to Cartesian grid before NL-CG based CS reconstruction. …”

Reputation scores suitable for different healthcare settings based on analysis. by Shamsudeen Sajna (22600978)

Subjects:

Performance of ENQUIRE’s gene normalization algorithm. by Luca Musella (19986312)

The Search process of the genetic algorithm. by Wenguang Li (6528113)

“…Firstly, the dataset was balanced using various sampling methods; secondly, a Stacking model based on GA-XGBoost (XGBoost model optimized by genetic algorithm) was constructed for the risk prediction of diabetes; finally, the interpretability of the model was deeply analyzed using Shapley values. …”

Algorithm design of XGBoost Cox model used in 1°P-CARDIAC full model. by Yekai Zhou (17285873)

Performance comparison of feature selection strategies for <i>S</i>. <i>cerevisiae</i> S phosphorylation site. by Chao Wang (146527)

Selection of the study population from the MIMIC-IV database. by Qiudie Liu (22655907)

Subjects:

Exploring the achievements and forecasting of SDG 3 using machine learning algorithms: Bangladesh perspective. by Md. Maeen Molla (20827041)

Selection of Optimum Clusters for the Sample Microscopic Image using Partition Entropy. by Claudia Barile (20678698)

Example framework for selecting an appropriate management solution for multi-species/objective forestry management. by Max D. Jones (6269006)

Histograms of the four features calculated from the base dataset and the sampled subset. by Matheus Viana da Silva (21433572)

Subjects:

Final results of site selection for the planning and layout of tourism and leisure facilities in the main urban area of Beijing. by Shifeng Wu (16612230)

Subjects:

Reshaping Industrial Maintenance with Machine Learning: Fouling Control Using Optimized Gaussian Process Regression by Francesco Negri (12992994)

Subjects:

Automatic Prediction of Molecular Properties Using Substructure Vector Embeddings within a Feature Selection Workflow by Son Gyo Jung (17913002)

“…The result underscores the importance of meticulous feature analysis and selection over a mere reliance on predictive modeling with a high degree of algorithmic complexity.…”

Decision tree algorithms. by Mahbub E. Sobhani (22278967)

“…We have used Random Forest, Bagging, and Boosting (AdaBoost) algorithms and have compared their performances. We have used decision tree (C4.5) as the base classifier of Random Forest and AdaBoost classifiers and naïve Bayes classifier as the base classifier of the Bagging model. …”

Block diagram for IoT-based irrigation system. by Gourab Saha (8987405)

Subjects: