Search alternatives:
based optimization » whale optimization (Expand Search)
binary studies » library studies (Expand Search), primary studies (Expand Search), literary studies (Expand Search)
binary series » primary series (Expand Search), webinar series (Expand Search), binary relief (Expand Search)
studies based » study based (Expand Search), species based (Expand Search)
series based » species based (Expand Search), genes based (Expand Search), scores based (Expand Search)
based optimization » whale optimization (Expand Search)
binary studies » library studies (Expand Search), primary studies (Expand Search), literary studies (Expand Search)
binary series » primary series (Expand Search), webinar series (Expand Search), binary relief (Expand Search)
studies based » study based (Expand Search), species based (Expand Search)
series based » species based (Expand Search), genes based (Expand Search), scores based (Expand Search)
-
101
30-Meter Resolution Dataset of Abandoned and Reclaimed Croplands in Inner Mongolia, China (2000-2022)
Published 2024“…This method enables precise classification of cultivation status and adopts a binary classification strategy with adaptive optimization, improving the efficiency of sample generation for the Random Forest algorithm. …”
-
102
Data_Sheet_1_Alzheimer’s Disease Diagnosis and Biomarker Analysis Using Resting-State Functional MRI Functional Brain Network With Multi-Measures Features and Hippocampal Subfield...
Published 2022“…Finally, we implemented and compared the different feature selection algorithms to integrate the structural features, brain networks, and voxel features to optimize the diagnostic identifications of AD using support vector machine (SVM) classifiers. …”
-
103
Supplementary Material 8
Published 2025“…</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.…”
-
104
DataSheet_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx
Published 2024“…<p>Cooking time is a crucial determinant of culinary quality of cassava roots and incorporating it into the early stages of breeding selection is vital for breeders. This study aimed to assess the potential of near-infrared spectroscopy (NIRS) in classifying cassava genotypes based on their cooking times. …”
-
105
Table_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx
Published 2024“…<p>Cooking time is a crucial determinant of culinary quality of cassava roots and incorporating it into the early stages of breeding selection is vital for breeders. This study aimed to assess the potential of near-infrared spectroscopy (NIRS) in classifying cassava genotypes based on their cooking times. …”
-
106
DataSheet_1_Exploring deep learning radiomics for classifying osteoporotic vertebral fractures in X-ray images.docx
Published 2024“…Logistic regression emerged as the optimal machine learning algorithm for both DLR models. …”
-
107
Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles
Published 2025“…</p><p dir="ltr">These biological metrics were used to define a binary toxicity label: entries were classified as toxic (1) or non-toxic (0) based on thresholds from standardized guidelines (e.g., ISO 10993-5:2009) and literature consensus. …”