Comparison of DR and FPR of UNSW-NB15. حسب Arshad Hashmi (13835488)

"…The model’s binary and multi-class classification accuracies on the UNSW-NB15 dataset are 99.56% and 99.45%, respectively. …"

Image1_Benchmark of Data Processing Methods and Machine Learning Models for Gut Microbiome-Based Diagnosis of Inflammatory Bowel Disease.eps حسب Ryszard Kubinski (12105983)

"…With an abundance of methods, there is a need to benchmark the performance and generalizability of various machine learning pipelines (from data processing to training a machine learning model) for microbiome-based IBD diagnostic tools. …"

Spontaneous ERG-based random forest model discriminates control and disease cases in rodent models of obesity and type 1 diabetes and predicts disease evolution in the type 1 diabe... حسب Ramsés Noguez Imm (6658637)

Table_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx حسب Massaine Bandeira e Sousa (7866242)

"…Two NIRs devices, the portable QualitySpec® Trek (QST) and the benchtop NIRFlex N-500 were used to collect spectral data. Classification of genotypes was carried out using the K-nearest neighbor algorithm (KNN) and partial least squares (PLS) models. …"

PathOlOgics_RBCs Python Scripts.zip حسب Ahmed Elsafty (16943883)

"…</p><p dir="ltr">In terms of classification, a second algorithm was developed and employed to preliminary sort or group the individual cells (after excluding the overlapping cells manually) into different categories using five geometric measurements applied to the extracted contour from each binary image mask (see PathOlOgics_script_2; preliminary shape measurements). …"

An exemplar procedure for activity flow modeling based on the direct and shortest paths at a network density of 15%. حسب Zhengdong Wang (35299)

Influence of underlying networks on the performance of Graph CNNs trained gene expression data. حسب Halima Alachram (11570633)

Influence of underlying networks on the performance of Graph CNNs trained gene expression data. حسب Halima Alachram (11570633)

Influence of underlying networks on the performance of Graph CNNs trained gene expression data. حسب Halima Alachram (11570633)

Influence of underlying networks on the performance of Graph-CNNs trained gene expression data. حسب Halima Alachram (11570633)

Models and Dataset حسب M RN (9866504)

"…</p><p dir="ltr"><br></p><p dir="ltr"><b>TJO (Tom and Jerry Optimization):</b><br>TJO is a nature-inspired metaheuristic algorithm that models the predator-prey dynamics of the cartoon characters Tom (predator) and Jerry (prey). …"

Fairness in Machine Learning: A Review for Statisticians حسب Xianwen He (22529252)

"…The discussion focuses on fairness in binary classification models using numerical tabular data, which serve as a foundation for addressing fairness in more complex algorithms. …"

Image_1_A predictive model based on random forest for shoulder-hand syndrome.JPEG حسب Suli Yu (14947807)

"…</p>Results<p>A binary classification model was trained based on 25 handpicked features. …"

Supplementary Material 8 حسب Nishitha R Kumar (19750617)

"…</li><li><b>XGboost: </b>An optimized gradient boosting algorithm that efficiently handles large genomic datasets, commonly used for high-accuracy predictions in <i>E. coli</i> classification.…"

Predicting childhood obesity using electronic health records and publicly available data حسب Robert Hammond (3631525)

"…</p><p>Methods and findings</p><p>We trained a variety of machine learning algorithms to perform both binary classification and regression. …"

Development of a Battery of <i>In Silico</i> Prediction Tools for Drug-Induced Liver Injury from the Vantage Point of Translational Safety Assessment حسب James Rathman (1632322)

"…Both human and mammalian data sets were processed using various learning algorithms, including artificial intelligence approaches. …"

Accessibility of translation initiation sites is the strongest predictor of heterologous protein expression in <i>E. coli</i>. حسب Bikash K. Bhandari (11524776)

Data for Exploring the Mechanism of Path-Creating Strategy for Latecomers: A Combined Approach of Econometrics and Causal Machine Learning حسب Yuanyang Teng (19096724)

"…TechCatchup-selected_features.xlsx is further processed data meet the requirements of binary classification and algorithm in the research. …"

DataSheet_2_MRI-Based Radiomics to Differentiate between Benign and Malignant Parotid Tumors With External Validation.pdf حسب Francesca Piludu (10706391)

DataSheet_1_MRI-Based Radiomics to Differentiate between Benign and Malignant Parotid Tumors With External Validation.xlsx حسب Francesca Piludu (10706391)