Correlation in the broadest sense is a measure of an association between variables. In
correlated data, the change in the magnitude of 1 variable is associated with a change in the …

Generative adversarial networks have gained a lot of attention in the computer vision
community due to their capability of data generation without explicitly modelling the …

Clustering is a solution for classifying enormous data when there is not any early knowledge
about classes. With emerging new concepts like cloud computing and big data and their vast …

Relative to quantitative methods traditionally used in accounting and finance, textual
analysis is substantially less precise. Thus, understanding the art is of equal importance to …

This succinct and jargon-free introduction to effect sizes gives students and researchers the
tools they need to interpret the practical significance of their results. Using a class-tested …

" This library is useful for practitioners, and is an excellent tool for those entering the field: it
is a set of computer vision algorithms that work as advertised."-William T. Freeman …

Significantly revised, the fifth edition of the most complete, accessible text now covers all
three approaches to structural equation modeling (SEM)--covariance-based SEM …

Publisher Description (unedited publisher data) An essential textbook for any student or
researcher in biology needing to design experiments, sampling programs or analyse the …

Since their inception in the 1930–1960s, the research disciplines of computational imaging
and machine learning have followed parallel tracks and, during the last two decades …

Nowadays, being in digital era the data generated by various applications are increasing
drastically both row-wise and column wise; this creates a bottleneck for analytics and also …