Android applications are developing rapidly across the mobile ecosystem, but Android
malware is also emerging in an endless stream. Many researchers have studied the …

Interestingness measures play an important role in data mining, regardless of the kind of
patterns being mined. These measures are intended for selecting and ranking patterns …

The field of machine learning has matured to the point where many sophisticated learning
approaches can be applied to practical applications. Thus it is of critical importance that …

Commonly used evaluation measures including Recall, Precision, F-Measure and Rand
Accuracy are biased and should not be used without clear understanding of the biases, and …

This paper gives an overview of some ways in which our understanding of performance
evaluation measures for machine-learned classifiers has improved over the last twenty …

BACKGROUND: The widespread availability of new computational methods and tools for
data analysis and predictive modeling requires medical informatics researchers and …

The process of identifying which records in two or more databases correspond to the same
entity is an important aspect of data quality activities such as data pre-processing and data …

Subgroup discovery is a data mining technique which extracts interesting rules with respect
to a target variable. An important characteristic of this task is the combination of predictive …

This paper investigates how to adapt standard classification rule learning approaches to
subgroup discovery. The goal of subgroup discovery is to find rules describing subsets of the …

In this paper, we provide a study on the use of tree kernels to encode syntactic parsing
information in natural language learning. In particular, we propose a new convolution kernel …