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estimation algorithm » optimization algorithms (Expand Search), maximization algorithm (Expand Search), detection algorithm (Expand Search)
codes optimization » codon optimization (Expand Search), model optimization (Expand Search), convex optimization (Expand Search)
robust estimation » pose estimation (Expand Search), risk estimation (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data codes » data code (Expand Search), data models (Expand Search), data model (Expand Search)
binary a » binary _ (Expand Search), binary b (Expand Search), hilary a (Expand Search)
a robust » _ robust (Expand Search)
estimation algorithm » optimization algorithms (Expand Search), maximization algorithm (Expand Search), detection algorithm (Expand Search)
codes optimization » codon optimization (Expand Search), model optimization (Expand Search), convex optimization (Expand Search)
robust estimation » pose estimation (Expand Search), risk estimation (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data codes » data code (Expand Search), data models (Expand Search), data model (Expand Search)
binary a » binary _ (Expand Search), binary b (Expand Search), hilary a (Expand Search)
a robust » _ robust (Expand Search)
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Individual Transition Label Noise Logistic Regression in Binary Classification for Incorrectly Labeled Data
Published 2021“…<p>We consider a binary classification problem in the case where some observations in the training data are incorrectly labeled. …”
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Determination of the Solute Content and Volumetric Properties of Binary Ionic Liquid Mixtures Using a Global Regularity of Molar Volume Expansion
Published 2021“…For instance, the water content, which is of great significance in IL studies, can easily be estimated using the proposed algorithm. By doing so, an overall AARD of 3.47% was obtained for the estimation of the water content of 68 binary systems. …”
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Algoritmo de clasificación de expresiones de odio por tipos en español (Algorithm for classifying hate expressions by type in Spanish)
Published 2024“…</li></ul><p dir="ltr"><b>File Structure</b></p><p dir="ltr">The code generates and saves:</p><ul><li>Weights of the trained model (.h5)</li><li>Configured tokenizer</li><li>Training history in CSV</li><li>Requirements file</li></ul><p dir="ltr"><b>Important Notes</b></p><ul><li>The model excludes category 2 during training</li><li>Implements transfer learning from a pre-trained model for binary hate detection</li><li>Includes early stopping callbacks to prevent overfitting</li><li>Uses class weighting to handle category imbalances</li></ul><p dir="ltr">The process of creating this algorithm is explained in the technical report located at: Blanco-Valencia, X., De Gregorio-Vicente, O., Ruiz Iniesta, A., & Said-Hung, E. (2025). …”
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QSAR model for predicting neuraminidase inhibitors of influenza A viruses (H1N1) based on adaptive grasshopper optimization algorithm
Published 2020“…The binary grasshopper optimization algorithm (BGOA) is a new meta-heuristic optimization algorithm, which has been used successfully to perform feature selection. …”
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Table 1_Provider fidelity in tuberculosis screening practices among adolescents and adults living with HIV in public health facilities in Tanzania: a cross-sectional evaluation.doc...
Published 2025“…Modified Poisson regression with robust variance was used to estimate prevalence ratios (PRs) to determine factors associated with two binary outcomes: (1) consistent TB screening over 12-month period, and (2) correct utilization of the screening tool. …”
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Table 2_Provider fidelity in tuberculosis screening practices among adolescents and adults living with HIV in public health facilities in Tanzania: a cross-sectional evaluation.doc...
Published 2025“…Modified Poisson regression with robust variance was used to estimate prevalence ratios (PRs) to determine factors associated with two binary outcomes: (1) consistent TB screening over 12-month period, and (2) correct utilization of the screening tool. …”
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Multicategory Angle-Based Learning for Estimating Optimal Dynamic Treatment Regimes With Censored Data
Published 2021“…Specifically, the proposed method obtains the optimal DTR via integrating estimations of decision rules at multiple stages into a single multicategory classification algorithm without imposing additional constraints, which is also more computationally efficient and robust. …”
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