Decision tree is one of the most widely used and practical methods in data mining and machine learning discipline. However, many discretization algorithms developed in this field focus on univariate only, which is inadequate to handle the critical problems especially owned by medical domain. In this paper, we propose a new multivariate discretization method called Multivariate Interdependent Di...

In this paper a model for the specification of the multivariate density of the transaction process is presented. The transaction process is characterized by four marks: price changes, transaction volumes, bid-ask spreads and trade durations. The resulting four dimensional density is decomposed into its conditional and unconditional densities. The density of price changes is modelled with an int...

Anonymization techniques that provide k-anonymity suffer from loss of quality when the data dimensionality is high. Microaggregation techniques are not an exception. Given a set of records, attributes are grouped into non-intersecting subsets and microaggregated independently. While this improves quality by reducing the loss of information, it usually leads to the loss of the k-anonymity proper...

This paper presents a novel methodology to detect a set of more suitable attributes that may potentially contribute to emerging faults of a wind turbine. The set of attributes were selected from one-year historical data for analysis. The methodology uses the k-means clustering method to process outlier data and verifies the clustering results by comparing quartiles of boxplots, and applies the ...

Mixtures provide a useful approach for relaxing parametric assumptions. Discrete mixture models induce clusters, typically with the same cluster allocation for each parameter in multivariate cases. As a more flexible approach that facilitates sparse nonparametric modeling of multivariate random effects distributions, this article proposes a kernel partition process (KPP) in which the cluster al...

The creations of models are essential for many knowledge disciplines to explain expected results. Modelling concept is well accepted in software engineering discipline. However, there is still a lacking integration of software process modelling and software process measurement by software engineers. This paper aims to portray the idea and result of integrating measurement in software process mo...

during recent years, determining appropriate strategy in the supply chain has become an important strategic issue. however, the nature of these decisions usually is complex and unstructured. to determine the best supply chain strategy, many quantitative and qualitative attributes such as cost, responsiveness and flexibility can be taken into account. in order to approximate the human subjective...