Computer-aided analysis of data from evaluation sheets of subjects with autism spectrum disorders
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Krzysztof Pancerz
,
Aneta Derkacz
Abstract
In this paper, we deal with the problem of the initial analysis of data from evaluation sheets of subjects with autism spectrum disorders (ASDs). In the research, we use an original evaluation sheet including questions about competencies grouped into 17 spheres. An initial analysis is focused on the data preprocessing step including the filtration of cases based on consistency factors. This approach enables us to obtain simpler classifiers in terms of their size (a number of nodes and leaves in decision trees and a number of classification rules).
Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
Research funding: None declared.
Employment or leadership: None declared.
Honorarium: None declared.
Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.
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©2016 Walter de Gruyter GmbH, Berlin/Boston
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Artikel in diesem Heft
- Frontmatter
- Review
- Cognitive robots in the development and rehabilitation of children with developmental disorders
- Opinion Paper
- Fuzzy-based computational simulations of brain functions – preliminary concept
- Original Articles
- Usefulness of the measurement of saccadic refixation in the diagnosis of attention-deficit hyperactivity disorder/hyperkinetic disorder in adults
- Computer-aided analysis of data from evaluation sheets of subjects with autism spectrum disorders
- Dissimilar sequence: similar structure of proteins
- Shortening and dispersion of single-walled carbon nanotubes upon interaction with mixed supramolecular compounds
- Oblique-viewing endoscope calibration in the diagnostics and treatment in the pelvis minor area
- Short Communication
- Molecular models of human visual pigments: insight into the atomic bases of spectral tuning
