Currently, we calculate statistics regarding classes and classifications. For classes, the results are grouped into three categories: totally unknown classes, partially known classes, totally known classes.
Considering X the number of classifications available, and K the number of known classifications, the categories are:
totally unknown classes (TU): K = 0
partially known classes (PK): 0 < K < X
totally known classes (TK): K = X
As can be seen, classes with a single known classification and classes with a single unknown classification are both registered as PK classes.
Considering this, we could create a new statistics for classes indicating the % of information (number of known classifications/number of classifications available) that this every class have.
By implementing this, it would be possible to discover the average amount of information discovered for classes. E.g., the average known percentage starts in 10% and ends in 90%, then 80% were increased.
Currently, we calculate statistics regarding classes and classifications. For classes, the results are grouped into three categories: totally unknown classes, partially known classes, totally known classes.
Considering X the number of classifications available, and K the number of known classifications, the categories are:
As can be seen, classes with a single known classification and classes with a single unknown classification are both registered as PK classes.
Considering this, we could create a new statistics for classes indicating the % of information (number of known classifications/number of classifications available) that this every class have.
By implementing this, it would be possible to discover the average amount of information discovered for classes. E.g., the average known percentage starts in 10% and ends in 90%, then 80% were increased.