Mainly understandable decision trees have been intended for perfect symbolic data. Conventional crisp decision trees (DT) are extensively used for classification purpose. However, there are still many issues particularly when we used the numerical (continuous valued) attributes. Structured continuouslabel classification is one type of classification in which the label is continuous in the data....

In the data-mining field, many learning methods — such as association rules, Bayesian networks, and induction rules (Grzymala-Busse & Stefanowski, 2001) — can handle only discrete attributes. Therefore, before the machine-learning process, it is necessary to re-encode each continuous attribute in a discrete attribute constituted by a set of intervals. For example, the age attribute can be trans...

Real-life data usually are presented in databases by real numbers. On the other hand, most inductive learning methods require a small number of attribute values. Thus it is necessary to convert input data sets with continuous attributes into input data sets with discrete attributes. Methods of discretization restricted to single continuous attributes will be called local, while methods that sim...

Structured patient data like Electronic Health Records (EHRs) are a valuable source for clinical research. However, the sensitive nature of such information requires some anonymisation procedure to be applied before releasing the data to third parties. Several studies have shown that the removal of identifying attributes, like the Social Security Number, is not enough to obtain an anonymous dat...

in the present work, a meshless method called finite point method (fpm) is developed to simulate the solidification process of a continuously cast steel bloom in both primary and secondary cooling regions. the method is based on the use of a weighted least-square interpolation procedure. a transverse slice of the bloom moving at casting speed is considered as the computational domain and two di...

The usage control (UCON) model demands for continuous control over objects of a system. Access decisions are done several times within a usage session and are performed on the basis of mutable attributes. Values of attributes in modern highly-dynamic and distributed systems sometimes are not up-to-date, because attributes may be updated by several entities and reside outside the system domain. ...

Monitoring HbA1c, the measurement for the average blood glucose level, is important to diabetic patients and may help improve their treatment. This study aims to train learning algorithms that predict patients with high variation in their HbA1c readings. Attributes in clinical data are often continuous, such as age, blood pressure, and lab tests. However, many machine learning algorithms work b...