Automatic Classification of Inspectional Categories: Multivariate Theories of Archaeological Data

Benfer, Robert A.; Benfer, Alice

doi:10.2307/280218

Cited by 17 publications

(6 citation statements)

References 25 publications

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“…Though low in some instances, results for these equations compare adequately and in some cases favorably to other techniques that use lower sample numbers or control samples derived from the same population used to create the equations or sectioning points (e.g., Iscan and Cotton, 1990;Baker et al, 1990). And, because this technique is founded on large control samples (N = 100 and N = 34) from different populations, the threat of statistical incest (Benfer and Benfer, 1981) is reduced and more stable results are generated.…”

Section: Equation Numbermentioning

confidence: 99%

Sex estimation using the first cervical vertebra

Marino

1995

American J Phys Anthropol

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The articular surfaces and vertebral foramen area of the first cervical vertebra are sexually dimorphic and can be used to sex complete or fragmentary specimens. Eight measurements were taken from the articular regions (superior and inferior) of 100 first cervical vertebrae from Terry collection specimens housed at the Smithsonian Institution. Seven regression and seven discriminant function equations were created that predict sex with 77-85% and 75-85% accuracy, respectively. In separate control tests, measurements from 100 first cervical vertebrae from Hamann-Todd collection individuals (Cleveland Museum of Natural History) and from 34 archaeological specimens were used with the Terry equations. The control samples were sexed with 60-85% accuracy.

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Section: Equation Numbermentioning

confidence: 99%

Sex estimation using the first cervical vertebra

Marino

1995

American J Phys Anthropol

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“…Later, it has been routinely employed in biological taxonomy, although it has also been criticized as unnecessarily complicated (Corruccini 1975). In archaeology, Kay (1975) adopted this method to chipped stone projectiles as a systematic measure of interrelatedness among sites, and Benfer & Benfer (1981) used it on stone darts from Texas. The latter analysis also presented a simplified graphical explanation of the method.…”

Section: Discriminant Analysismentioning

confidence: 98%

Automatic versus intuitive and impressionistic classification of Norwegian spearheads from A.D. 550–1100

Solberg

1986

Norwegian Archaeological Review

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Norwegian spearheads from the Merovingian and Viking periods were classified by an automatic multivariate statistical method (discriminant analysis) and the results compared to those of an intuitive (436 spearheads) and an impressionistic classification method (1199 spearheads), the latter based upon measurements of well-defined attributes and results of x-ray examinations. A set of measurements of each of 338 well-preserved spearheads (prototype specimens) served as the basis for the automatic classification. A fair correlation (87.2%) was observed between the results of the automatic and the intuitive classifications. A less favourable correlation (64%) was observed between the results of the automatic and impressionistic methods, mainly due to many incomplete (poorly preserved) spearheads which were inadequately classified by the automatic method. Accordingly, the automatic method was regarded as inferior to the impressionistic. In high quality spearheads with pattern-welded blades, decorated sockets, and homogeneous proportional attributes, however, a close correlation was observed between the automatic and the intuitive/impressionistic classifications. Most likely, these spearheads are derived from highly specialized workshops. The automatic classification method seems, therefore, useful in tracing manufacture from such workshops.

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“…It follows that, in general, one is not certain if a given variable will be informative about such structure. To get around this uncertainty, one measures many aspects of the objects (e.g., the measurement schemes of Benfer and Benfer 1981;Gunn and Prewitt 1975;Thomas 1970 for projectile points) in order to ensure that what needs to be measured is most likely embedded in the set of measurements. This, however, is the undoing of clustering algorithms as has been shown by simulated example (Read 1989a) and by mathematical/statistical argument (Read 1992).…”

Section: Multiple Measurementsmentioning

confidence: 99%

A Method for Taxonomic Typology Construction and an Example: Utilized Flakes

Read

Russell

1996

Am. antiq.

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This paper considers problems inherent in constructing typologies based on subdividing artifacts using clustering algorithms that assume a paradigmatic structure (as do most, if not all, currently used algorithms) and presents an alternative method based on a taxonomic, rather than a paradigmatic, structure for the artifact classes. The method is exemplified by analysis of an assemblage of utilized flakes from a series of late prehistoric habitation sites in the central highlands of Peru. These flakes were previously analyzed using more intuitive, traditional methods but without identifying any satisfactory groupings within the assemblage. Similarly, paradigmatically based clustering algorithms applied to the entire data set and using the several variables measured over these flakes were also unable to extract meaningful groupings. In contrast, the method presented here was able to (1) construct a partition of the flake assemblage into groups that also made intuitive sense to the practitioner, (2) have functional interpretation assignable through a model of transmission of forces from agent to object acted on, and (3) produce units differentially occurring across the several subsites from which the utilized flakes were obtained, i.e., units that add another dimension to the analysis of activities represented by the archaeological assemblage. Although demonstrated with utilized flakes, the method has general application.

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Automatic Classification of Inspectional Categories: Multivariate Theories of Archaeological Data

Cited by 17 publications

References 25 publications

Sex estimation using the first cervical vertebra

Sex estimation using the first cervical vertebra

Automatic versus intuitive and impressionistic classification of Norwegian spearheads from A.D. 550–1100

A Method for Taxonomic Typology Construction and an Example: Utilized Flakes

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