Results 241 to 250 of about 636,655 (299)

Identification of Compassion Fatigue Risk Profiles in Veterinarians: Implications for Prevention and Professional Well-Being. [PDF]

open access: yesEur J Investig Health Psychol Educ
Cobos Sanchiz D   +3 more
europepmc   +1 more source

Absolute Cluster Validity

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020
The application of clustering involves the interpretation of objects placed in multi-dimensional spaces. The task of clustering itself is inherently submitted to subjectivity, the optimal solution can be extremely costly to discover and sometimes even unreachable or nonexistent. This fact introduces a trade-off between accuracy and computational effort,
Felix Iglesias   +2 more
openaire   +3 more sources

Validating Cluster Assignments

Psychological Reports, 2000
In the absence of a statistically based assessment of cluster assignments of observations in terms of their similarity along selected variables the validity of a set of clusters could be developed if clusters withstand both empirical scrutiny and “make sense” to expert informants.
D J, Ketchen, G T, Hult
openaire   +3 more sources

Cluster Validation

2009
Spacecrafts orbiting a selected suite of planets and moons of our solar system are continuously sending long sequences of data back to Earth. The availability of such data provides an opportunity to invoke tools from machine learning and pattern recognition to extract patterns that can help to understand geological processes shaping planetary surfaces.
Ricardo Vilalta, Tomasz Stepinski
openaire   +2 more sources

On Clustering Validation Techniques

Journal of Intelligent Information Systems, 2001
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Halkidi, Maria   +2 more
openaire   +2 more sources

Multi-Objective Clustering and Cluster Validation

2006
This chapter is concerned with unsupervised classification, that is, the analysis of data sets for which no (or very little) training data is available. The main goals in this data-driven type of analysis are the discovery of a data set's underlying structure, and the identi.cation of groups (or clusters) of homogeneous data items - a process commonly ...
Handl, Julia, Knowles, Joshua
openaire   +3 more sources

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