According to the results of the research, the social anxieties of the participants show a significant difference according to the class variable
. The social anxiety levels of 9th grade students are higher than the social anxiety levels of 10th and 11th grade students.
[alpha] is the regularization parameter, U = ([u.sub.1], [u.sub.2], ..., [u.sub.n]) is unclassified data, and c = ([c.sub.1], [c.sub.2], ..., [c.sub.m]) is the arbitrary value of the class variable
. We can achieve a relatively accurate result of classifications which can meet the practical application by using multidimensional Bayesian classifier.
The decision tree can be seen as a set of compact rules in a tree format, where, in each node, an attribute variable is introduced; and in the leaves (or end nodes) we have a label of the class variable
or a set of probabilities for each class label.
Because of the independence assumption, in a Bayesian network for incident detection, the class variable
INC must get links to all the attribute variables; therefore each and every piece of information about attribute variables can be made use of to update the incident probability.
At the same time, tree augmented naive Bayesian classifier, in Tan, class variables
no parent node and each attribute variables to class variables
and most another attribute variables of the parent node and all variables constitute the whole network structure is tree structure (Sonmez, E., Aydin, E., Turkez, H., Ozbek, E., Togar, B., Meral, K., ...
The latent class variable
"c" is used to model the unknown heterogeneity, whereas, observed variables, that are known to introduce heterogeneity, are treated as covariates.
When the points of Assertiveness and Anxiety Levels are compared in line with the class variable
, a statistically significant difference is observed (p>0.05, Tablo 3).
3) The coefficients of the lower and higher categories of the social class variable
This means that under the above independence assumptions, the conditional distribution over the class variable
C can be expressed like this:
The question we wanted to address in these analyses was whether the latent class variable
differentially moderated fathers' and mothers' support in predicting youth social initiative, such that a group of youth could be identified, for whom the previously reported general effect (i.e., greater prediction of social initiative by reports of fathers' support compared to reports of mothers' support) did not hold.
In this analysis, within-time latent class fitting was used primarily to explore and describe the latent class variable
, contentment in out-of home care, at both time points.