Clustering and classification are two important techniques of data mining. Classification is a supervised learning problem of assigning an object to one of several pre-defined categories based upon the attributes of the object. While, clustering is an unsupervised learning problem that group objects based upon distance or similarity. Each group is known as a cluster. In this paper we make use o...

Flett, Vredenburg, and Krames (1995) claim that their data support the view that the apparent instability in distress among college students is artifactual. However, they have merely demonstrated that distress among college students is an unstable phenomena. Their argument that changes in distress scores have statistical rather than substantive explanations erroneously assumes that instability ...

The classification and regression trees (CART) possess the advantage of being able to handlelarge data sets and yield readily interpretable models. In spite to these advantages, they are alsorecognized as highly unstable classifiers with respect to minor perturbations in the training data.In the other words methods present high variance. Fuzzy logic brings in an improvement in theseaspects due ...

Background: Monitoring serves to maintain physiologic variables within normal limits and when a parameter crosses a set threshold, an alarm is triggered. Therefore, this study aimed to determine whether alarm limits are properly adjusted in the neonatal intensive care unit (NICU) by nursing staff or not.Methods: The data concerning alarm limits corresponding to the three shifts of nursing...

The work aims at investigating and establishing if Aggregational Gaussianity, (AG) is in the dynamics of petroleum prices. This AG aspect phenomenon which empirical distribution log-returns tends to normality (or as time scale over returns are calculated increases). In order achieve this, price series was tested for arch effects. addition, tests were carried out using qualitative (graphical) ap...