Classed Data

Classed data can be any alphanumeric value ("red", "-78", "large", "3.14159", "0", "absent", "dentate", etc.). Classed data are used to identify a feature without implying any innate ordinal value. Using classed data, OptiPath will try to sort artifacts to preserve temporal proximity of features of the same class (with the same nominal value) but will make no attempt to sort or order the classes. For example, with nominal feature values of "red", "blue" and "green", OptiPath would try to group all of the "red" artifacts together, and similarly the "blue" and "green", but would be indifferent between an ordering that put "red" before "blue" before "green" and one that put "blue" before "red" before "green". The same would hold true if you were to name your classes "1", "2", "3" and "4" in which case OptiPath would be indifferent between 1-2-3-4 and 4-1-3-2.

The feature parameter Data can be used to specify that a feature should use classed data.

Classed data is usually associated with nominal seriation (where a data value simply identifies a feature value or class without implying an ordering among classes).

Classed data is not appropriate for frequency seriation and optimal path seriation (where measured data is more appropriate) nor for occurrence seriation and discrete seriation (where ranked data is more appropriate).

For classed data, the feature parameter Ranks can take on only the value 0 or 1. If the value of Ranks is 0, there is no limit to the number of ranks or classes the data might take on.

To see the effect on the raw data of setting various feature parameters, including the Data parameter, look at processed data in the Values table.