Because of its many advantages, the use of decision trees has become an increasingly popular alternative predictive tool for building classification and regression models. Its origins date back for about five decades where the algorithm can be broadly described by repeatedly partitioning the...

Pruning decision tree is an effective method to avoid the phenomena of overfitting. Various pruning methods have been proposed in many literatures. This paper gives a new decision tree pruning method based on Rough Set Theory (RST). According to the concept of explicit region in literature, this...

A tree is said to be -magic if there exits a super magic labeling such that then the vertices of is partioned into three color classes , , so that the vertex labels in ∈ {1,2,3} are all consecutive labels. In this paper we have given -magic labeling of a class of trees with diameter four that...

Rapid technological development and progress lead to the need for better and more efficient education which should prepare the applicant for increasingly flexible labour market. The goal of this research is to create models for prediction of student's efficacy, compare them, find the key factors...

In this paper by modifying the definition of edge-magic labelling for trees we give further strength to the edge-magic tree conjecture. We have shown the complete binary trees and comets (2-stars) are strong edge-magic

This paper proposes a set of new methods to estimate inequality of opportunity based on conditional inference regression trees. It illustrates how these methods represent a substantial improvement over existing empirical approaches to measure inequality of opportunity. First, the new methods...

In the data mining and machine learning fields, forecasting the direction of price change can be generally formulated as a supervised classfii cation. This paper attempts to predict the direction of daily changes of the Nasdaq Composite Index (NCI) and of the Standard & Poor's 500 Composite...

We propose a set of new methods to estimate inequality of opportunity based on conditional inference regression trees. In particular, we illustrate how these methods represent a substantial improvement over existing empirical approaches to measure in equality of opportunity. First, they minimize...

Low visibility conditions enforce special procedures that reduce the operational flight capacity at airports. Accurate and probabilistic forecasts of these capacity-reducing lowvisibility procedure (lvp) states help the air traffic management to optimize flight planning and regulation. In this...