Feature selection process. حسب Balraj Preet Kaur (20370832)

Reproducing kernel-based semiparametric functional smoothed score estimation with binary responses حسب Meichen Liu (8168148)

Texas Rio Grande Valley Red–crowned Parrot predicted general use habitat distribution as determined via a consensus-based feature ensemble of 12 calibrated (binary presence/absence... حسب Elise Varaela Voltura (17592996)

Texas Rio Grande Valley Red–crowned Parrot predicted roost site habitat distribution as determined via a consensus-based feature ensemble of 12 calibrated (binary presence/absence)... حسب Elise Varaela Voltura (17592996)

Texas Rio Grande Valley Red–crowned Parrot predicted nest site habitat distribution as determined via a consensus-based feature ensemble of 12 calibrated (binary presence/absence)... حسب Elise Varaela Voltura (17592996)

The overlap of Texas Rio Grande Valley Red–crowned Parrot predicted general use, roost site, and nest site habitat distributions as determined using consensus-based feature ensembl... حسب Elise Varaela Voltura (17592996)

<i>hi</i>PRS algorithm process flow. حسب Michela C. Massi (14599915)

"…The sequences can include from a single SNP-allele pair up to a maximum number of pairs defined by the user (<i>l</i>_max). <b>(C)</b> The whole training data is then scanned, searching for these sequences and deriving a re-encoded dataset where interaction terms are binary features (i.e., 1 if sequence <i>i</i> is observed in <i>j</i>-th patient genotype, 0 otherwise). …"

Design and implementation of the Multiple Criteria Decision Making (MCDM) algorithm for predicting the severity of COVID-19. حسب Jiaqing Luo (10975030)

"…<p>(A). The MCDM algorithm-Stage 1. Preprocessing, this stage is the process of refining the collected raw data to eliminate noise, including correlation analysis and feature selection based on P values. …"

Flowchart scheme of the ML-based model. حسب Noshaba Qasmi (20405009)

"…<b>I)</b> Testing data consisting of 20% of the entire dataset. <b>J)</b> Optimization of hyperparameter tuning. <b>K)</b> Algorithm selection from all models. …"

Identification and quantitation of clinically relevant microbes in patient samples: Comparison of three k-mer based classifiers for speed, accuracy, and sensitivity حسب George S. Watts (7962206)

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)

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.…"

Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles حسب Soham Savarkar (21811825)

"…Details on the data sourcing process, prompt engineering strategies for large language model (LLM)-based extraction, and validation protocols are provided in the Supplementary Information section.…"

Seed mix selection model حسب Bethanne Bruninga-Socolar (10923639)

"…<em>Conservation Letters,</em> <em>10</em>, 105-111. doi: 10.1111/conl.12261</p> <p><br></p> <p>Scrucca, L. (2013). GA: A Package for Genetic Algorithms in R. …"

Flow diagram of the automatic animal detection and background reconstruction. حسب David Tadres (9120564)

"…(E) The threshold value is calculated based on the histogram: it is the mean of the image subtracted by 4 (optimal value defined by trial and error). …"