Decomposition-based Classifier Chains for Multi-Dimensional Classification

2021 ◽  
pp. 1-1
Author(s):  
Bin-Bin Jia ◽  
Min-Ling Zhang
Keyword(s):  
Dimensional Classification ◽  
Classifier Chains

Diagnoses, Dimensions, and DSM-5

2010 ◽  
pp. 254-279
Author(s):  
Thomas A. Widiger ◽  
Maryanne Edmundson
Keyword(s):  
Substance Use ◽  
Mental Disorders ◽  
Paradigm Shift ◽  
Empirical Support ◽  
Statistical Manual ◽  
Diagnostic And Statistical Manual ◽  
Dsm 5 ◽  
Dimensional Classification ◽  
Diagnosis And Classification

The Diagnostic and Statistical Manual of Mental Disorders, Third Edition (DSM-III) is often said to have provided a significant paradigm shift in how psychopathology is diagnosed. The authors of DSM-5 have the empirical support and the opportunity to lead the field of psychiatry to a comparably bold new future in diagnosis and classification. The purpose of this chapter is to address the validity of the categorical and dimensional models for the classification and diagnosis of psychopathology. Considered in particular will be research concerning substance use disorders, mood disorders, and personality disorders. Limitations and concerns with respect to a dimensional classification of psychopathology are also considered. The chapter concludes with a recommendation for a conversion to a more quantitative, dimensional classification of psychopathology.

scholarly journals Towards a contemporary approach for understanding personality pathology in developmental context: An integrative model

2021 ◽  
pp. 1-10
Author(s):  
Melody R. Altschuler ◽  
Robert F. Krueger
Keyword(s):  
Personality Disorders ◽  
Personality Pathology ◽  
Integrative Model ◽  
Research Domain Criteria ◽  
Developmental Context ◽  
Dimensional Classification ◽  
Developmental Theories ◽  
Underlying Mechanisms ◽  
Research Domain

Abstract Traditional categorical approaches to classifying personality disorders are limited in important ways, leading to a shift in the field to dimensional approaches to conceptualizing personality pathology. Different areas of psychology – personality, developmental, and psychopathology – can be leveraged to understand personality pathology by examining its structure, development, and underlying mechanisms. However, an integrative model that encompasses these distinct lines of inquiry has not yet been proposed. In order to address this gap, we review the latest evidence for dimensional classification of personality disorders based on structural models of maladaptive personality traits, provide an overview of developmental theories of pathological personality, and summarize the Research Domain Criteria (RDoC) initiative, which seeks to understand underlying mechanisms of psychopathology. We conclude by proposing an integrative model of personality pathology development that aims to elucidate the developmental pathways of personality pathology and its underlying mechanisms.

scholarly journals A heuristic in A* for inference in nonlinear Probabilistic Classifier Chains

2017 ◽  
Vol 126 ◽  
pp. 78-90 ◽  
Author(s):  
Deiner Mena ◽  
José Ramón Quevedo ◽  
Elena Montañés ◽  
Juan José del Coz
Keyword(s):  
Probabilistic Classifier ◽  
Classifier Chains

scholarly journals Student Performance Prediction with Optimum Multilabel Ensemble Model

2021 ◽  
Vol 30 (1) ◽  
pp. 511-523
Author(s):  
Ephrem Admasu Yekun ◽  
Abrahaley Teklay Haile
Keyword(s):  
High School Students ◽  
Prediction Model ◽  
Student Performance ◽  
Performance Prediction ◽  
Transformation Method ◽  
Classification Task ◽  
Support Vector ◽  
School Students ◽  
K Nearest Neighbors ◽  
Classifier Chains

Abstract One of the important measures of quality of education is the performance of students in academic settings. Nowadays, abundant data is stored in educational institutions about students which can help to discover insight on how students are learning and to improve their performance ahead of time using data mining techniques. In this paper, we developed a student performance prediction model that predicts the performance of high school students for the next semester for five courses. We modeled our prediction system as a multi-label classification task and used support vector machine (SVM), Random Forest (RF), K-nearest Neighbors (KNN), and Multi-layer perceptron (MLP) as base-classifiers to train our model. We further improved the performance of the prediction model using a state-of-the-art partitioning scheme to divide the label space into smaller spaces and used Label Powerset (LP) transformation method to transform each labelset into a multi-class classification task. The proposed model achieved better performance in terms of different evaluation metrics when compared to other multi-label learning tasks such as binary relevance and classifier chains.

scholarly journals UV Spectral Classification of B Stars

1985 ◽  
Vol 111 ◽  
pp. 411-413
Author(s):  
Janet Rountree ◽  
George Sonneborn ◽  
Robert J. Panek
Keyword(s):  
Classification System ◽  
Classification Criteria ◽  
High Dispersion ◽  
Spectral Classification ◽  
Early Type ◽  
B Stars ◽  
Dimensional Classification ◽  
Early Type Stars ◽  
Comprehensive Classification

Previous studies of ultraviolet spectral classification have been insufficient to establish a comprehensive classification system for ultraviolet spectra of early-type stars because of inadequate spectral resolution. We have initiated a new study of ultraviolet spectral classification of B stars using high-dispersion IUE archival data. High-dispersion SWP spectra of MK standards and other B stars are retrieved from the IUE archives and numerically degraded to a uniform resolution of 0.25 or 0.50 Å. The spectra (in the form of plots or photowrites) are then visually examined with the aim of setting up a two-dimensional classification matrix. We follow the method used to create the MK classification system for visual spectra. The purpose of this work is to examine the applicability of the MK system (and in particular, the set of standard stars) in the ultraviolet, and to establish classification criteria in this spectral region.

Prospects for the classification of mental disorders of children and adolescents

2008 ◽  
Vol 23 (7) ◽  
pp. 481-485 ◽  
Author(s):  
M.H. Schmidt ◽  
J. Sinzig
Keyword(s):  
Mental Disorders ◽  
Children And Adolescents ◽  
Classification Systems ◽  
General Question ◽  
Specific Information ◽  
Specific Symptom ◽  
Trade Offs ◽  
Dimensional Classification ◽  
Dsm V

AbstractSuggestions for classification of mental disorders of children and adolescents in DSM-V and ICD-11 have been made, which differ strongly from the current descriptive approach of dimensional classification.These suggestions even comprise a dichotomized system for health care as well as for scientific purposes.Nevertheless it is obvious that we are far behind an “etiological” classification, so that trade-offs have necessarily to be made in DSM-V and ICD-11.Appropriate proposals concern the strict separation of disorders that are typical for children and adolescents as well as for adults.Furthermore a differentiation of diagnosis for infants, toddlers and preschool children is required in both classification systems. As far as it is relevant for treatment, combined diagnosis in DSM-V and subthreshold diagnosis as well as coding-possibilities for findings in molecular biology should be permitted.As personality disorders should only be diagnosed after the age of 16, it is recommended to dimensionally classify personality traits that are pathognomonic for specific symptom patterns and of prognostic relevance.DSM-V and ICD-11 should allow age-specific information on axis-IV. The article discusses the general question of how relational disorders respectively disturbances should be classified and include furthermore special recommendations concerning ICD and DSM categories.

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