Arnis Kirshners

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This paper provides application analysis of e-services available on the joint state and municipal e-service portal . The research is performed using a combination of time series analysis and data mining techniques. Time series analysis has enabled the determination of the count of clusters that represent services classification by application(More)
A joint analysis of continuous (time series demand observations) and discrete (well-describing parameters) data is studied. Such data mining techniques as data collection, preprocessing, clustering analysis, and classification are considered. Upon continuous data preprocessing and clustering, images of possible sales development are constructed. A new(More)
21 The paper presents a pilot research on the application of clinical decision support systems in a atrophic 22 gastritis screening task. Two different DSS learning strategies have been tested – a standalone classifier 23 and classifier ensemble application. Such classification algorithms as C4.5, CART, JRip and Naive Bayes 24 were used as base classifiers.(More)
The article analyzes various clustering approaches that are used in gene expression tasks. The chosen approaches are portrayed and examined from the viewpoint of use of data mining clustering algorithms. The article provides a short description of working principles and characteristics of the examined methods and algorithms and the data sets used in the(More)
This paper addresses the task of short historical time series and discrete descriptive parameters processing aimed at making demand forecast only on the basis of new product describing parameters. Several data mining methods are used for data processing including data extraction, pre-processing, cluster analysis and classification. Data preparation for data(More)
This work considers the results of laboratory investigations carried out to create a system for predicting cardiac necrosis risks that would be based on algorithms and procedures of data mining. Continuous data that indicated changes in the heartbeat and descriptive characteristics of the test animals were used. The procedures of data mining used included(More)
This article examines several data mining approaches that perform short time series analysis. The basis of the methods is formed by clustering algorithms with or without modifications. The proposed methods implement short time series analysis when the numbers of the observations are not equal and the historical information is short. The inspected approaches(More)
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