Methods underlying cluster analysis are very useful in data analysis, especially when the processed volume of data is very large, so that it becomes impossible to extract essential information, unless specific instruments are used to summarize and structure the gross information. In this...

The aim of artificial intelligence is to discover mechanisms of adaptation in a changing environment with utilisation of intelligence, for instance in the ability to exclude unlikely solutions. Artificial intelligence methods have extensive application in different fields such as medicine,...

A tanulmányban a Weka adatbányászati szoftver használata és a szövegosztályozás alapelvei kerülnek bemutatásra. Egy gyakorlati példán keresztül, amiben Internetről letöltött 4000 db ingatlanhirdetési szöveget dolgoztam fel, több szövegosztályozási módszert megvizsgáltam....

Highly imbalanced data sets are those where the class of interest is rare. In this paper, we compare the performance of several common data mining methods, logistic regression, discriminant analysis, Classification and Regression Tree (CART) models, C5, and Support Vector Machines (SVM) in...

Transportation demand modeling has evolved in scope, theory, and practice in the many decades since the US Bureau of Public Roads pioneered home interview transportation studies in metropolitan households in the early 1940s. The major currents of these developments are discussed in the present...

Workforce analytics (i.e., statistical analysis, modeling and mining of HR data) is particularly important in service industries. Service industries are people-intensive and the knowledge and expertise of the people within an organization is a strategic resource critical for success. Performance...

This paper demonstrates the hazard of “stir-fry” regressions, which are used extensively in financial research to produce desirable results by reporting only one or a small number of regressions out of the tens or hundreds that are typically estimated. It is shown, by using data on the...

Multivariate adaptive regression splines (MARS) has become a popular data mining (DM) tool due to its flexible model building strategy for high dimensional data. Compared to well-known others, it performs better in many areas such as finance, informatics, technology and science. Many studies...

In this paper, an algorithm for finding piecewise linear boundaries between pattern classes is developed. This algorithm consists of two main stages. In the first stage, a polyhedral conic set is used to identify data points which lie inside their classes, and in the second stage we exclude...

Based on debris-flow inventories and using a geographical information system, the susceptibility models presented here take into account fluvio-morphologic parameters, gathered for every first-order catchment. Data mining techniques on the morphometric parameters are used, to work out and test...