boolean analysis造句

There is a close connection between Boolean analysis and knowledge spaces.
Boolean analysis has some relations to other research areas.
In contrast Boolean analysis offers a way to construct such dependencies from data.
Bart and Airasian ( 1974 ) use Boolean analysis to establish logical implications on a set of Piagetian tasks.
There are several attempts to use boolean analysis, especially item tree analysis to construct knowledge spaces from data.
It's difficult to find boolean analysis in a sentence. 用boolean analysis造句挺难的

Since the basic work of Flament ( 1976 ) a number of different methods for Boolean analysis have been developed.
Methods of Boolean analysis are used in a number of social science studies to get insight into the structure of dichotomous data.
The main difference between Boolean analysis and the extraction of association rules in data mining is the interpretation of the extracted implications.
Bart and Krus ( 1973 ) use, for example, Boolean analysis to establish a hierarchical order on items that describe socially unaccepted behavior.
Janssens ( 1999 ) used a method of Boolean analysis to investigate the integration process of minorities into the value system of the dominant culture.
Methods of Boolean analysis can be used to construct a knowledge structure from data ( for example, Theuns, 1998 or Schrepp, 1999 ).
The goal of a Boolean analysis is to extract implications from the data which are ( with the exception of random errors in the response behavior ) true for all rows in the data set.
The main difference between both research areas is that Boolean analysis concentrates on the extraction of structures from data while knowledge space theory focus on the structural properties of the relation between a knowledge structure and the logical formulas which describe it.