Kumar, "Impact of distance measures on the performance of clustering algorithms," in Intelligent Computing, Networking, and Informatics, ed: Springer, 2014, pp. 183-190.V. Kumar, J. Chhabra, and D. Kumar, "Impact of distance measures on the performance of clustering algorithms," in ...
To achieve unbiased estimates of both the signal and the scale parameter (σt) when data are contaminated by errors, the use of robust estimators is required. One of the most popular measures of robustness of a statistical procedure is the breakdown point, which represents the proportion of out...
application of different clustering algorithms generally results in different sets of cluster formation, it is important to evaluate the performance of these methods in terms of accuracy and validity of the clusters, and also the time required to generate them, using appropriate performance measures. ...
The performance can be evaluated in terms of accuracy and validity of the clusters, and also the time required to generate them, using appropriate performance measures. In this paper, we have analysed the performance of Self-Organizing neural network based clustering and k-Means clustering using ...
The performance of a randomized metaheuristic algorithm can be divided into efficiency and effectiveness measures. The efficiency relates to the algorithm’s speed of finding accurate solutions, convergence, and computation. On the other hand, effectiveness relates to the algorithm’s capability of ...
The Fowlkes-Mallows function measures the similarity of two clustering of a set of points. It may be defined as the geometric mean of the pairwise precision and recall.Mathematically,FMS=TP(TP+FP)(TP+FN)−−−−−−−−−−−−−−−−−−−√FMS=TP(TP+FP...
This graph shows the evaluation performance of a method at all classification thresholds. The curve plots the true positive rate versus the false positive rate, whereas the AUC measures the entire two-dimensional area underneath the ROC curve from 0 to 1. The AUC ranges from 0.0 to 1.0. For...
Jensen’s inequality relative to matrix-valued measures J. Math. Anal. Appl. (2007) S. Alpert et al. Image segmentation by probabilistic bottom-up aggregation and cue integration IEEE Trans. Pattern Anal. Machine Intell. (2012) J. Tighe, S. Lazebnik, SuperParsing: scalable nonparametric ima...
The method used to determine the track score, discussed in the following, applies a robust approach based largely on sim- ple measures of the track quality. Clusters assigned to a track increase the track score according to configurable weight fractions reflecting the intrinsic resolutions and ...
Ratings—estimates of individuals' job performance made by supervisors, peers, or others familiar with their performance—are by far the most often used criterion measure (Landy and Farr 1980). Objective measures such as turnover and production rates will also be discussed. 3.1 Performance Ratings ...