This theoretical-review article contributes to the discussion on individual energy savings by developing a hypothetical classification of interventions and linking them to socio-psychological factors affecting the transition points of four phases of behavior change (predecision, preaction, action, and postaction).
We sought to redress this by developing a natural classification for the fold and using it as guide for exploring the tempo of its evolutionary radiations and details of its functional adaptations.
With the advent of new technologies like brain mapping, neuroimaging, genetics, epigenetics, proteomics, neurotransmitters, metabolic assessment, neuropsychology, brain-computer-interface, many researchers and clinicians expressed the hope to advance the field by developing a biologically guided psychiatric classification, diagnostic system and treatment recommendation [ 1, 7].
To accomplish this aim, we propose a breast cancer prognosis based classification algorithm by developing a virtual chromosome (VC) consisting of two components (correlation-factor and penalized-factor), which are used to extract our prognostic gene signature that consists of 79 genes.
Classification is implemented by developing a model with existing records by using sample data.
SVMs are binary classifiers and multi-class classification is realized by developing an SVM for each pair of classes.
For example, Nie et al. reported six features selected from morphology and texture descriptors by an artificial neural network and developed a classification model for computer-aided diagnosis [ 30].
Ramsar Convention, the Convention on Wetlands of International Importance, developed a classification system used by many countries to guide protection and wise use of wetlands.
The present study explores the chemical attributes of diverse ionic liquids responsible for their cytotoxicity in a rat leukemia cell line (IPC-81) by developing predictive classification as well as regression-based mathematical models.
As a result, we can discriminate the small difference of similarity between lower limbs by developing SVM classification model to recognize the right-left gait patterns accurately.
