Table 8_Identifying network state-based Parkinson’s disease subtypes using clustering and support vector machine models.xlsx by Benedictor Alexander Nguchu (9984371)

Table 3_Identifying network state-based Parkinson’s disease subtypes using clustering and support vector machine models.xlsx by Benedictor Alexander Nguchu (9984371)

Image 1_Identifying network state-based Parkinson’s disease subtypes using clustering and support vector machine models.tiff by Benedictor Alexander Nguchu (9984371)

Table 5_Identifying network state-based Parkinson’s disease subtypes using clustering and support vector machine models.xlsx by Benedictor Alexander Nguchu (9984371)

Table 7_Identifying network state-based Parkinson’s disease subtypes using clustering and support vector machine models.xlsx by Benedictor Alexander Nguchu (9984371)

Contactless Mobile Payment Framework and Software Application: Computer Programming Code and Data by Hisham AbouGrad (21228341)

Subjects:

Performance metrics of various algorithms. by Pritam Chakraborty (9261302)

“…Initially, preference algorithms identify the most important features in various machine learning models, including logistic regression, K-nearest neighbor, decision tree, support vector machine (linear kernel), support vector machine ( RBF kernel), neural networks, etc. …”

Algorithm comparison - top performances. by Pritam Chakraborty (9261302)

“…Initially, preference algorithms identify the most important features in various machine learning models, including logistic regression, K-nearest neighbor, decision tree, support vector machine (linear kernel), support vector machine ( RBF kernel), neural networks, etc. …”

Ranking of features for each algorithm. by Pritam Chakraborty (9261302)

“…Initially, preference algorithms identify the most important features in various machine learning models, including logistic regression, K-nearest neighbor, decision tree, support vector machine (linear kernel), support vector machine ( RBF kernel), neural networks, etc. …”

code_2 by Olga Ovtsarenko (20432033)

Corporate network anomaly detection methodology utilizing machine learning algorithms by Nazerke Baisholan (22048322)

IbM code graphical description by Irina Ofiteru (14716360)

Comparison of ROC curve between deep learning and 12 handcrafted features using four machine learning algorithms. by Rui-Si Hu (5337227)

Pseudo-code for the study design model. by Jianpeng Zhang (528185)

Classification results of ML-based algorithms for literary works—A comparison of accuracy. by Arta Misini (19929042)

Classification results of ML-based algorithms for newsroom columns—A comparison of accuracy. by Arta Misini (19929042)

XAI based LIME algorithm results for solar power generation forecasting model. by Rizk M. Rizk-Allah (18625751)

Subjects:

Analysis of elements of emergency resource scheduling model in chemical industry park. by Yuhang Wang (332111)

Source Code for Comparative Study of Search Trees Implemented in Java by Mohammed Alaa Ala'anzy (21711464)

Multi-material topology optimization using scaled boundary finite element method by Mohammed Saif Zamiruddin Siddiqui (22384884)

“…<p>This work introduces the use of Scaled Boundary Finite Element Method (SBFEM) in Multi-Material Topology Optimization (MMTO) problems, which is new in the literature. …”