Search alternatives:
identification algorithm » classification algorithm (Expand Search), detection algorithm (Expand Search)
from identification » early identification (Expand Search), _ identification (Expand Search), wide identification (Expand Search)
codon optimization » wolf optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
identification algorithm » classification algorithm (Expand Search), detection algorithm (Expand Search)
from identification » early identification (Expand Search), _ identification (Expand Search), wide identification (Expand Search)
codon optimization » wolf optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
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Confusion metrics using LR-HaPi algorithm.
Published 2024“…This study is conducted on data collected from Twitter via its API, and an annotation scheme is proposed to categorize tweets into binary classes (propaganda and non-propaganda). …”
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Confusion metrics using MNB-HaPi algorithm.
Published 2024“…This study is conducted on data collected from Twitter via its API, and an annotation scheme is proposed to categorize tweets into binary classes (propaganda and non-propaganda). …”
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Confusion metrics using DT-HaPi algorithm.
Published 2024“…This study is conducted on data collected from Twitter via its API, and an annotation scheme is proposed to categorize tweets into binary classes (propaganda and non-propaganda). …”
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Confusion metrics using SVM-HaPi algorithm.
Published 2024“…This study is conducted on data collected from Twitter via its API, and an annotation scheme is proposed to categorize tweets into binary classes (propaganda and non-propaganda). …”
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Proposed framework for propaganda identification.
Published 2024“…This study is conducted on data collected from Twitter via its API, and an annotation scheme is proposed to categorize tweets into binary classes (propaganda and non-propaganda). …”
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Framework for data extraction from Twitter.
Published 2024“…This study is conducted on data collected from Twitter via its API, and an annotation scheme is proposed to categorize tweets into binary classes (propaganda and non-propaganda). …”
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Identification and quantitation of clinically relevant microbes in patient samples: Comparison of three k-mer based classifiers for speed, accuracy, and sensitivity
Published 2019“…We tested the accuracy, sensitivity, and resource requirements of three top metagenomic taxonomic classifiers that use fast k-mer based algorithms: Centrifuge, CLARK, and KrakenUniq. Binary mixtures of bacteria showed all three reliably identified organisms down to 1% relative abundance, while only the relative abundance estimates of Centrifuge and CLARK were accurate. …”
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Supplementary file 1_Comparative evaluation of fast-learning classification algorithms for urban forest tree species identification using EO-1 hyperion hyperspectral imagery.docx
Published 2025“…</p>Methods<p>Thirteen supervised classification algorithms were comparatively evaluated, encompassing traditional spectral/statistical classifiers—Maximum Likelihood, Mahalanobis Distance, Minimum Distance, Parallelepiped, Spectral Angle Mapper (SAM), Spectral Information Divergence (SID), and Binary Encoding—and machine learning algorithms including Decision Tree (DT), K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Random Forest (RF), and Artificial Neural Network (ANN). …”
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Natural language processing and machine learning algorithm to identify brain MRI reports with acute ischemic stroke
Published 2019“…</p><p>Conclusions</p><p>Supervised ML based NLP algorithms are useful for automatic classification of brain MRI reports for identification of AIS patients. …”
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Recent work related to propaganda.
Published 2024“…This study is conducted on data collected from Twitter via its API, and an annotation scheme is proposed to categorize tweets into binary classes (propaganda and non-propaganda). …”
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Feature statistical analysis.
Published 2024“…This study is conducted on data collected from Twitter via its API, and an annotation scheme is proposed to categorize tweets into binary classes (propaganda and non-propaganda). …”
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Wordcloud of non-propaganda tex.
Published 2024“…This study is conducted on data collected from Twitter via its API, and an annotation scheme is proposed to categorize tweets into binary classes (propaganda and non-propaganda). …”