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  2. Clustering high-dimensional data - Wikipedia

    en.wikipedia.org/wiki/Clustering_high...

    Clustering high-dimensional data is the cluster analysis of data with anywhere from a few dozen to many thousands of dimensions.Such high-dimensional spaces of data are often encountered in areas such as medicine, where DNA microarray technology can produce many measurements at once, and the clustering of text documents, where, if a word-frequency vector is used, the number of dimensions ...

  3. Group concept mapping - Wikipedia

    en.wikipedia.org/wiki/Group_concept_mapping

    The resulting maps display the individual statements in two-dimensional space with more similar statements located closer to each other, and grouped into clusters that partition the space on the map. The Concept System software also creates other maps that show the statements in each cluster rated on one or more scales, and absolute or relative ...

  4. Hierarchical Taxonomy of Psychopathology - Wikipedia

    en.wikipedia.org/wiki/Hierarchical_taxonomy_of...

    Signs, symptoms, and maladaptive traits and behaviors are grouped into homogeneous components- constellations of closely related symptom manifestations; for example, fears of working, reading, eating, or drinking in front of others form performance anxiety cluster.

  5. Multiple complex developmental disorder - Wikipedia

    en.wikipedia.org/wiki/Multiple_complex...

    Various websites contain various diagnostic criteria. At least three of the following categories should be present. Co-occurring clusters of symptoms must also not be better explained by being symptoms of another disorder such as experiencing mood swings due to autism, cognitive difficulties due to schizophrenia, and so on.

  6. Self-organizing map - Wikipedia

    en.wikipedia.org/wiki/Self-organizing_map

    These clusters then could be visualized as a two-dimensional "map" such that observations in proximal clusters have more similar values than observations in distal clusters. This can make high-dimensional data easier to visualize and analyze.

  7. Medoid - Wikipedia

    en.wikipedia.org/wiki/Medoid

    We use the medoid to group “clusters” of data, which is obtained by finding the element with minimal average dissimilarity to all other objects in the cluster. [23] Although the visualization example used utilizes k-medoids clustering, the visualization can be applied to k-means clustering as well by swapping out average dissimilarity with ...

  8. Child PTSD Symptom Scale - Wikipedia

    en.wikipedia.org/wiki/Child_PTSD_Symptom_Scale

    The Child PTSD Symptom Scale (CPSS) is a free checklist designed for children and adolescents to report traumatic events and symptoms that they might feel afterward. [1] The items cover the symptoms of posttraumatic stress disorder , specifically, the symptoms and clusters used in the DSM-IV. Although relatively new, there has been a fair ...

  9. Dimensional Obsessive-Compulsive Scale - Wikipedia

    en.wikipedia.org/wiki/Dimensional_Obsessive...

    The Dimensional Obsessive-Compulsive Scale (DOCS) is a 20-item self-report instrument that assesses the severity of Obsessive-Compulsive Disorder (OCD) symptoms along four empirically supported theme-based dimensions: (a) contamination, (b) responsibility for harm and mistakes, (c) incompleteness/symmetry, and (d) unacceptable (taboo) thoughts. [1]