Sentence examples for sum of data points from inspiring English sources

Table 1 Physicochemical properties investigated in this study; each column contains the number of data points collected for each ILs' class along with the overall sum of data points   Viscosity (cPa) KOW Solubility (g/L) Enthalpy of fusion (kJ/mol) Imidazolium 20 20 6 7 Ammonium 24 7 1 4 Phosphonium 46 0 0 0 Pyridinium 23 1 8 13 Pyrrolidinium 5 0 1 1 Sulfonium 8 0 3 5 Sum 126 28 19 30.

This can be as simple as a sum of data points, or as complicated as finding the average of certain data points and comparing them to other averages.

The performance of the STREAM method with respect to computational costs and quality of the clustering, measured in terms of sum of squared distances (SSQ) of data points from the assigned clusters centers, is also studied, in particular in comparison with K-means, providing good theoretical and experimental results.

This is achieved by summing the number of data points which are greater than or equal to the IS of interest relative to the number of data points that are assigned to lower IS's (Fig. 2 for an example).

Rather than minimize the sum of squared residuals for all data points included in ordinary least squares regression, LTS minimizes the sum of squared residuals for a subset of data points that minimizes the sum of squared residuals to remove the influence of outliers from the regression.

The peak intensities from the H T2 experiments were determined by summing over an adequate grid of data points centered at the peak maxima.

K-means cluster analysis uses an algorithm that minimizes the within sum of squares to identify clusters of data points.

A form suitable for non-linear models is the Generalized Prediction Error criterion [ 27]: where γ is the effective number of parameters in the network, E is the error sum of squares, N is the number of data points in the training set and σ is the variance of the noise of the data.

A CF is a group of closely related data points and is defined based on three variables (N, LS, SS) that summarize information related to the data points in the CF. (1) N = Number of data points in the CF. LS = Linear sum of the N vector data points.

(5 where WRSS is the weighted residual sum of squares, p is the number of model parameters, and n is the number of data points in a TAC.

where N is the number of data points, M is the number of unknown parameters and RSS is the residual sum of squares obtained from the fitting routine.