k-nearest neighbors algorithm
PulseAugur coverage of k-nearest neighbors algorithm — every cluster mentioning k-nearest neighbors algorithm across labs, papers, and developer communities, ranked by signal.
No coverage in the last 90 days.
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AI framework detects foot anomalies to aid diabetic ulcer prevention
Researchers have developed a baseline feasibility study for an unsupervised anomaly detection framework using wearable foot sensors to help prevent diabetic foot ulcers. The study applied Isolation Forest and K-Nearest …
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Machine learning effectively detects fake news using textual and linguistic features
This research paper explores the effectiveness of textual and linguistic content features in detecting fake news, particularly during the COVID-19 pandemic. The study utilized traditional machine learning models like Ra…
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Manokhin Probability Matrix offers new framework for classifier quality
Researchers have introduced the Manokhin Probability Matrix, a new diagnostic framework designed to evaluate the quality of probabilistic predictions from classifiers. This framework separates reliability and resolution…
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Researchers explore data symmetries to improve noisy dataset selection for ML
Researchers have developed a new method to identify optimal subsets of training data, particularly when dealing with label noise. This approach leverages data symmetries and invariance properties to improve the accuracy…
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New ensemble learning framework predicts groundwater heavy metal pollution
Researchers have developed a new ensemble machine learning framework to predict groundwater heavy metal pollution in the Densu Basin. The study integrated response transformations, including a Gaussian copula, with six …
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New framework enables training ML models on encrypted data using homomorphic encryption
Researchers have developed a privacy-preserving framework for training machine learning models using homomorphic encryption. This approach allows computations on encrypted data, safeguarding sensitive information throug…
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New pipeline enhances white blood cell classification amid domain shifts
Researchers have developed a hierarchical ensemble inference pipeline to improve the accuracy of automated white blood cell classification, particularly in the presence of domain shifts. This method utilizes a memory-au…
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AI study uses clustering to find patterns in social media use and mental health
Researchers have developed a clustering-based approach using unsupervised machine learning to analyze the relationship between social media usage and mental health. The study segmented 551 participants into six distinct…
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New RE-IRL framework infers investor preferences from market actions
Researchers have developed a new framework using Relative Entropy Inverse Reinforcement Learning (RE-IRL) to infer investor reward functions from their observed actions and market data. This approach is designed for sit…
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New research introduces Fermat distance for high-dimensional semi-supervised classification
Researchers have developed new methods for high-dimensional semi-supervised classification by utilizing the Fermat distance, a metric sensitive to data density and cluster assumptions. The proposed weighted k-nearest ne…