… features selection method is proposed for HAR. In general, the HAR consists of series of
steps including pre-processing, human detection, features … Thereafter, it extracts features such …

… feature selection technique based on Euclidean distance and joint entropy with PCA. The
proposed selection … First, calculate the Euclidean distance between fused features and select …

… a unique feature ordering and selection technique called Feature Ranking and Subset Selection
based on Euclidean distance (… Many feature selection techniques have explored for the …

… , selecting features in the raw data, are difficult to implement. This paper proposes feature
selection based on Euclidean Distance … approach can select a robust feature subset to build …

This article suggests the method to distinguish normal persons and a Parkinson’s disease
patients by their sole pressure sensor data using NEWFM (Neural Network with Weighted …

… In this paper, we propose two Euclidean distance-based anomaly detection schemes for …
-based feature selection method to choose the distinguishing optimal feature data subset as …

… feature selection and classifier design that should be paid more attention. In this paper, we
focus on the first point. In general, the methods of feature selection … The first selection method …

… distance used for this purpose is a Euclidean distance, which is a special case of Minkowski
metric or non-Euclidean … values including the popular Euclidean distance to observe the …

… We evaluate several distance-based feature selection methods … feature selection methods.
Experimental results using several … The Euclidean distance between examples of concepts is …

… prediction need the feature selection method for target class related feature in order to …
Euclidean distance based feature selection for fault detection prediction model. First, the features …