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Advances in Data Analysis and Classification

Theory, Methods, and Applications in Data Science

Advances in Data Analysis and Classification OnlineFirst articles

11-09-2020 | Regular Article

Editable machine learning models? A rule-based framework for user studies of explainability

So far, most user studies dealing with comprehensibility of machine learning models have used questionnaires or surveys to acquire input from participants. In this article, we argue that compared to questionnaires, the use of an adapted version of …

02-09-2020 | Regular Article

A comparison of instance-level counterfactual explanation algorithms for behavioral and textual data: SEDC, LIME-C and SHAP-C

Predictive systems based on high-dimensional behavioral and textual data have serious comprehensibility and transparency issues: linear models require investigating thousands of coefficients, while the opaqueness of nonlinear models makes things …

02-09-2020 | Regular Article

A novel dictionary learning method based on total least squares approach with application in high dimensional biological data

In recent years dictionary learning has become a favorite sparse feature extraction technique. Dictionary learning represents each data as a sparse combination of atoms (columns) of the dictionary matrix. Usually, the input data is contaminated by …

02-09-2020 | Regular Article

Mixtures of factor analyzers with scale mixtures of fundamental skew normal distributions

Mixtures of factor analyzers (MFA) provide a powerful tool for modelling high-dimensional datasets. In recent years, several generalizations of MFA have been developed where the normality assumption of the factors and/or of the errors were relaxed …

30-08-2020 | Regular Article Open Access

The GNG neural network in analyzing consumer behaviour patterns: empirical research on a purchasing behaviour processes realized by the elderly consumers

The paper sheds light on the use of a self-learning GNG neural network for identification and exploration of the purchasing behaviour patterns. The test has been conducted on the data collected from consumers aged 60 years and over, with regard to …

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About this journal

The international journal Advances in Data Analysis and Classification (ADAC) is designed as a forum for high standard publications on research and applications concerning the extraction of knowable aspects from many types of data. It publishes articles on such topics as structural, quantitative, or statistical approaches for the analysis of data; advances in classification, clustering, and pattern recognition methods; strategies for modeling complex data and mining large data sets; methods for the extraction of knowledge from data, and applications of advanced methods in specific domains of practice. Articles illustrate how new domain-specific knowledge can be made available from data by skillful use of data analysis methods. The journal also publishes survey papers that outline, and illuminate the basic ideas and techniques of special approaches.

Supported by the International Federation of Classification Societies, and funded by the Italian, German, and Japanese Classification Societies (CLADAG, GfKl, JCS).

Officially cited as: Adv Data Anal Classif

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