Samples can be clustered into groups based on their distance in the descriptor space by using such methods as hierarchical clustering (Johnson, 1967).
(ii) Clustering case samples based on the binary vectors by conventional methods as hierarchical clustering or K-means, which obtains two sample clusters.
In a recent review [12], R Sharan et al described two main classes of the network-based methods for predicting protein functions: direct methods such as neighborhood counting based method [18],Graph theoretic methods [19], [20]; module-assisted methods such as hierarchical clustering-based methods [21], [22], graph clustering methods [23], [24].
The results of this study show that using AE technique with an appropriate clustering method such as hierarchical model could be an applicable tool for structural health monitoring of composite structures.
Different from other clustering methods, such as hierarchical clustering and k-means, the density clustering methods do not cluster all the nodes in PPI network.
These two methods have been consistently reported to perform better than other methods, such as hierarchical clustering (Chen et al., 2002; Datta and Datta, 2003; Thalamuthu et al., 2006).
Thus, we chose to stay in line with the methods used to construct the original models and refrain from further sophisticated methods such as hierarchical modelling and shrinkage of coefficients.
In the last decades, methods such as hierarchical cluster analysis (HCA), discriminant analysis (DA), correlation analysis, and principal component analysis (PCA) have become accepted in identifying variations and sources of groundwater pollution (Zhang et al. 2012; Gordana et al. 2014).
In this study, selected statistical methods such as hierarchical cluster analysis (HCA) and analysis of variance (ANOVA) were used to determine the spatio-temporal variations of hydrochemical elements and to identify the origin of these elements in surface water of Koudiat Medouar, East Algeria.
