ML algorithms used in this study. by Toheeb Salahudeen (21368040)

“…Although the precise relationship with mitochondrial pathways remains elusive, recent advances in machine learning present an avenue for further investigation. …”

TreeMap 2016 Stand Size Code Algorithm (Image Service) by U.S. Forest Service (17476914)

“…We used a random forests machine-learning algorithm to impute the forest plot data to a set of target rasters provided by Landscape Fire and Resource Management Planning Tools (LANDFIRE: https://landfire.gov). …”

Confusion Matrix for Subspace algorithm (3000 Learning Cycles) providing insight into the performance evaluation of Subspace algorithm. by Sadia Nazim (21440115)

DCA curves on testing data of eight machine learning algorithm models. by Xin Liu (43569)

ROC curves on testing data of eight machine learning algorithm models. by Xin Liu (43569)

Calibration curves on testing data of eight machine learning algorithm models. by Xin Liu (43569)

Machine learning algorithm validation performance comparison plot. by Hilman Nordin (20615178)

Open-source code for the Spatial Optimization Model for Land Use (SSFLA-MLAS) by bowen pang (21837359)

Subjects:

Surface plots of the used Physics machine learning models in the present work. by Akshansh Mishra (21001499)

Contour Plot of Physics machine learning models used in the present work. by Akshansh Mishra (21001499)

Shortest path calculation using Dijkstra’s Algorithm. by Qing Zhu (349093)

Subjects:

Machine learning prediction algorithm flow chart. by Ahmad M. Al-Omari (20460931)

Convergence curves for the applied algorithms. by Eslam Hamouda (5172083)

Visualization of mean absolute SHAP values for conditional algorithm for each class. by Sadia Nazim (21440115)

Visualization of mean absolute SHAP values for Interventional algorithm for each class. by Sadia Nazim (21440115)

Comparative analysis of off-policy PPO algorithm and on-policy algorithm on the a) CSMAR and b) MorningStar datasets. by Cai Yuanqing (22513351)

Comparison of parameter ranges used for Latin hypercube sampling (LHS) in [29] and genetic algorithms (GA) in the present work. by Jyotika Bahuguna (729510)

Algorithmic experimental parameter design. by Chuanxi Xing (20141665)

“…Finally, we derive an off-grid sparse model for the reconstructed signal by exploiting sparsity in the null domain and use Bayesian learning to compute the maximum a posteriori probability of the source signal, thus achieving DOA estimation. …”

Typical results of using the WSINDy algorithm for example problem L.3 in Table 2 with the library presented in Table 3, , and 50 points in time. by Rainey Lyons (22806496)

Confusion matrix for RUSBoost algorithm (3000 Learning Cycles) highlights the classification accuracy across different classes. by Sadia Nazim (21440115)