Losing V, Hammer B, Wersing H (2015) Interactive online learning for obstacle classification on a mobile robot. In: International joint conference on neural networks, pp 1–8 Losing V, Hammer B, Wersing H (2016) KNN classifier with self adjusting memory for heterogeneous concept drift. In:...
Patient data was classified considering either all 4 muscles simultaneously, 2 muscles within the same extremity (EXT versus APB), or 2 muscles from different extremities (EXT versus TA).In all cases, RF classifiers performed best and kNN second best. The highest performances were achieved on ...
classifier then becomes a model which, given a set of feature values, predicts the class to which the input data might belong. Figure4shows a general approach for applying classification techniques. The performance of a classifier in its ability to predict the correct class is measured in terms ...
There were many statistical algorithms or computational methods, and of which some included data-mining analysis [59], hidden Markov analysis [60], cluster analysis (similarity-based method) [61], kernel-based data fusion analysis [62], machine learning [63], KNN classification algorithm [64] ...
K-Nearest Neighbors (KNN) classifier: The k-Nearest Neighbor (k-NN) technique is a typical non-parametric classifier applied in machine learning (Lin et al., 2015). The idea of these techniques is to name an unlabelled data sample to the class of its k nearest neighbors (where k is an...
Statistical Evaluation of Local Alignment Features Predicting Allergenicity Using Supervised Classification Algorithms Background: Recently, two promising alignment-based features predicting food allergenicity using the k nearest neighbor (kNN) classifier were reported. The... D Soeria-Atmadja,A Zorzet,Gustaf...
In Ref. [25], self-organizing map and KNN were used for cooling fan bearing monitoring. In Ref. [26], the K-means cluster method was utilized to obtain cluster center points, and an anomaly score was calculated based on the distance from center points. In Ref. [27], one class SVM ...
Nextarticlein issue Keywords Network classification Machine learning Deep learning Deep packet inspection Traffic monitoring 1. Introduction Reliance on the Internet has significantly increased around the globe, making it an essential part of both individuals' and corporates' daily operations. This increase...
has been done by five ML classifiers (kNN, SVM, RF, DNN, eXtreme Gradient Boosting–XGBoost), and the best-performing one was the XGBoost. Altogether, developing numerous AI algorithms and larger data sizes have been devoted to the LBVS growth and acted as a useful tool in drug R&D [92...
Sentence level: In this level of analysis, each sentence is analyzed and finding with a corresponding polarity. This is highly useful when a document has a wide range and mix of sentiments associated with it (Yang and Cardie2014). This classification level is associated with subjective classificat...