Real-life data sets sometimes miss some values. The incomplete data needs specialized algorithms or preprocessing that allows the use of the algorithms for complete data. The paper presents a comparison of various techniques for handling incomplete data in the neuro-fuzzy system ANNBFIS. The crucial procedure in the creation of a fuzzy model for the neuro-fuzzy system is the partition of the in...

Nuclear magnetic resonance (NMR) is a physical phenomenon based upon the quantum mechanical magnetic properties of an atoms nucleus. Thereby NMR spectroscopy is a technique to obtain physical, chemical and structural information about molecules. Recent research is focused on the analysis of small molecules, e.g. metabolites by NMR or in a combination of NMR and electro spray ionization mass spe...

Time series data is an important data type in many different application scenarios. Consequently, there are a great variety of approaches for analyzing time series data. Within these approaches different strategies for cleaning, segmenting, representing, normalizing, comparing, and aggregating time series data can be found. When combining these operations, the time series analysis preprocessing...

The paper is focused on an examination of the use of entropy in the field of web usage mining. Entropy creates an alternative possibility of determining the ratio of auxiliary pages in the session identification using the Reference Length method. The experiment was conducted on two different web portals. The first log file was obtained from a course of virtual learning environment web portal. T...

Numerous gel-based and nongel-based technologies are used to detect protein changes potentially associated with disease. The raw data, however, are abundant with technical and structural complexities, making statistical analysis a difficult task. Low-level analysis issues (including normalization, background correction, gel and/or spectral alignment, feature detection, and image registration) a...

We introduce a user-friendly graphical data preprocessing application based on Hive, one of the well known opensource distributed warehouse systems. It is comfortable, and easy to use for preprocessing purposes, but to prove usability of this application, we created measurement a framework to ensure precise results. These results show that our application has outstanding scaling capability in t...

All analyses of version archives have one phase in common: the preprocessing of data. Preprocessing has a direct impact on the quality of the results returned by an analysis. In this paper we discuss four essential preprocessing tasks necessary for a fine-grained analysis of CVS archives: (a) data extraction, (b) transaction recovery, (c) mapping of changes to fine-grained entities, and (d) dat...

In this paper, several ways to handle missing data, e.g. removing cases, mean imputation, and multiple imputation, are described and discussed. The Pima-Indians-Diabetes data set is used as a case study. This particular data set is interesting to use since it has not been obvious to all users that it actually contains a substantial amount of missing data. The data set is described in detail and...

The past two decades of microRNA (miRNA) research has solidified the role of these small non-coding RNAs as key regulators of many biological processes and promising biomarkers for disease. The concurrent development in high-throughput profiling technology has further advanced our understanding of the impact of their dysregulation on a global scale. Currently, next-generation sequencing is the ...