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Remote sensing in field crop monitoring: A comprehensive review of sensor systems, data analyses and recent advances
The key elements that underpin food security require the adaptation of agricultural systems
to support productivity increases while minimizing inputs and the adverse effects of climate …
to support productivity increases while minimizing inputs and the adverse effects of climate …
Effects of distance measure choice on k-nearest neighbor classifier performance: a review
The K-nearest neighbor (KNN) classifier is one of the simplest and most common classifiers,
yet its performance competes with the most complex classifiers in the literature. The core of …
yet its performance competes with the most complex classifiers in the literature. The core of …
kNN Classification: a review
The k-nearest neighbors (k/NN) algorithm is a simple yet powerful non-parametric classifier
that is robust to noisy data and easy to implement. However, with the growing literature on …
that is robust to noisy data and easy to implement. However, with the growing literature on …
[HTML][HTML] Enhancing the early detection of chronic kidney disease: a robust machine learning model
Clinical decision-making in chronic disorder prognosis is often hampered by high variance,
leading to uncertainty and negative outcomes, especially in cases such as chronic kidney …
leading to uncertainty and negative outcomes, especially in cases such as chronic kidney …
[HTML][HTML] Machine learning approaches to modeling and optimization of biodiesel production systems: State of art and future outlook
One of the main limitations to the economic sustainability of biodiesel production remains
the high feedstock cost. Modeling and optimization are crucial steps to determine if …
the high feedstock cost. Modeling and optimization are crucial steps to determine if …
Solving the problem of the K parameter in the KNN classifier using an ensemble learning approach
This paper presents a new solution for choosing the K parameter in the k-nearest neighbor
(KNN) algorithm, the solution depending on the idea of ensemble learning, in which a weak …
(KNN) algorithm, the solution depending on the idea of ensemble learning, in which a weak …
[PDF][PDF] Distance and Similarity Measures Effect on the Performance of K-Nearest Neighbor Classifier–A
The K-nearest neighbor (KNN) classifier is one of the simplest and most common classifiers,
yet its performance competes with the most complex classifiers in the literature. The core of …
yet its performance competes with the most complex classifiers in the literature. The core of …
[HTML][HTML] A comparative study of supervised machine learning approaches to predict patient triage outcomes in hospital emergency departments
Background The inconsistency in triage evaluation in emergency departments (EDs) and the
limitations in practice within the standard triage tools among triage nurses have led …
limitations in practice within the standard triage tools among triage nurses have led …
Robust Distance Measures for kNN Classification of Cancer Data
R Ehsani, F Drabløs - Cancer informatics, 2020 - journals.sagepub.com
The k-Nearest Neighbor (k NN) classifier represents a simple and very general approach to
classification. Still, the performance of k NN classifiers can often compete with more complex …
classification. Still, the performance of k NN classifiers can often compete with more complex …
Advancing peptide-based cancer therapy with AI: in-depth analysis of state-of-the-art AI models
Anticancer peptides (ACPs) play a vital role in selectively targeting and eliminating cancer
cells. Evaluating and comparing predictions from various machine learning (ML) and deep …
cells. Evaluating and comparing predictions from various machine learning (ML) and deep …