The run time for each algorithm in seconds. by Edward Antonian (21453161)

“…Finally, we use the Laplace approximation to determine a lower bound for the out-of-sample prediction error and derive a scalable expression for the marginal variance of each prediction. …”

Comparison of different optimization algorithms. by Hang Zhao (143592)

Subjects: “…crayfish optimization algorithm…”

FIS image analysis using the semi-automatic algorithm. by Anna Demchenko (18449439)

Summary of the metrics of the different trained algorithms that performed best in the Testing process for each dataset. by Jaime B. Matas-Bustos (21772430)

Algorithmic experimental parameter design. by Chuanxi Xing (20141665)

“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”

Schematic diagram of the experimental algorithm. by Ronghua Meng (20978441)

Subjects:

Summary of the metrics of the different trained algorithms based on mean and 95% confidence intervals (calculated using t-Student) for the Testing process in each dataset. by Jaime B. Matas-Bustos (21772430)

Spatial spectrum estimation for three algorithms. by Chuanxi Xing (20141665)

“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”

ML algorithms in cyber security. by Abdullah Asım Yılmaz (20715311)

Summary of the metrics of the different trained models foreach algorithm in each split for each dataset. by Jaime B. Matas-Bustos (21772430)

Schematic representation of semi-automated algorithm for organoids analyzing. by Anna Demchenko (18449439)

Kidney Transplant Biopsy-derived signature matrix of 18 cell phenotypes (KTB18) for deconvolution using the CIBERSORTx algorithm by Alexis Varin (20591600)

“…<p dir="ltr"><a href="https://www.nature.com/articles/s41587-019-0114-2" rel="noreferrer" target="_blank">CIBERSORTx</a> is an algorithm, accessible through a <a href="https://cibersortx.stanford.edu/index.php" rel="noreferrer" target="_blank">web portal</a>, designed to infer the cellular composition of bulk RNA-seq or microarray data, referred to as "mixture files". …”

Algorithm process. by Wei Cui (92129)

The actual training effect of four algorithms on original photo data (All images are original images taken by the author). by Xiaojun Wang (50332)

Subjects:

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

Subjects:

The construction process of the FCM clustering algorithm. by Xini Fang (20861990)

Subjects:

Effects of Nash equilibrium speed changes with the non-sensory motor algorithm on encounters, agent numbers, and payoffs. by Hiroyuki Ichijo (13891153)

Subjects:

Effects of Nash equilibrium attack and defense behaviors with the sensory–motor algorithm on encounters, agent numbers, and payoffs. by Hiroyuki Ichijo (13891153)

Subjects:

Credit Card Fraud Classification Using Applied Machine Learning – A Comparative Study of 24 ML Algorithms by Kelechi Amamba (21022064)

“…<p dir="ltr">Credit Card Fraud Classification Using Applied Machine Learning – A Comparative Study of 24 ML Algorithms</p><p dir="ltr">This study describes an empirical evaluation of 24 machine learning models, including Logistic Regression, Decision Trees, Random Forests, Support Vector Machines and Neural Networks using a highly imbalanced fraud dataset that reflects the real-world where the data was culled from. …”

Processed results from ECG data with the P-T algorithm. by Daehyun Kwon (11985629)