Search alternatives:
models optimization » process optimization (Expand Search), wolf optimization (Expand Search), codon optimization (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), based optimization (Expand Search)
binary simple » binary image (Expand Search), binary people (Expand Search)
kcp models » top models (Expand Search), cg models (Expand Search), qsp models (Expand Search)
models optimization » process optimization (Expand Search), wolf optimization (Expand Search), codon optimization (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), based optimization (Expand Search)
binary simple » binary image (Expand Search), binary people (Expand Search)
kcp models » top models (Expand Search), cg models (Expand Search), qsp models (Expand Search)
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Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment
Published 2019“…The MapReduce parallel programming model on the Hadoop platform is used to perform an adaptive fusion of hue, local binary pattern (LBP) and scale-invariant feature transform (SIFT) features extracted from images to derive optimal combinations of weights. …”
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Models and Dataset
Published 2025“…</p><p dir="ltr"><br></p><p dir="ltr"><b>RAO (Rao Optimization Algorithm):</b><br>RAO is a parameter-less optimization algorithm that updates solutions based on simple arithmetic operations involving the best and worst individuals in the population. …”
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Supplementary Material 8
Published 2025“…</p><h4><b>10 Supervised machine learning classifiers for </b><b><i>E.coli</i></b><b> genome analysis:</b></h4><ol><li><b>Logistic regression (LR): </b> A simple yet effective statistical model for binary classification, such as predicting antibiotic resistance or susceptibility in <i>E. coli</i>.…”
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Predictive Analysis of Mushroom Toxicity Based Exclusively on Their Natural Habitat.
Published 2025“…Optimization with GridSearchCV corroborated this stagnation, identifying a simple linear model (C=0.05, gamma='scale') as the optimal configuration, indicating that the additional complexity of nonlinear kernels did not confer predictive gains. …”