Robert Brzeski

Parametric Optimization of the Selected Classifiers in Binary Classification

The conception of classification is one of the major aspects in data processing. Conducted research present comparison of chosen classifiers’ results of classification for a few data sets. All data were chosen from these available on UCI Machine Learning Repository web site. During realization of research, the optimization process of the results of classification was made on the modifiable parameters for particular classifiers. In this work, gathered result of classification was presented as well as conclusion and possibility of future work.

Adjusting Parameters of the Classifiers in Multiclass Classification

The article presents the results of the optimization process of classification for five selected data sets. These data sets contain the data for the realization of the multiclass classification. The article presents the results of initial classification, carried out by dozens of classifiers, as well as the results after the process of adjusting parameters, this time obtained for a set of selected classifiers. At the end of article, a summary and the possibility of further work are provided.

The Data Dimensionality Reduction in the Classification Process Through Greedy Backward Feature Elimination

The article presents the author’s algorithm of dimensionality reduction of used data set, realized through Greedy Backward Feature Elimination. Results of the dimensionality reduction are verified in the process of classification for 2 selected data sets. These data sets contain the data for the realization of the multiclass classification. The article presents not only a description of the algorithm but also an example and the results of classification, carried out by selected classifier before and after the process of dimensionality reduction. At the end of article, a summary and the possibility of further work are provided.

E–LT Concept in a Light of New Features of Oracle Data Integrator 12c Based on Data Migration within a Hospital Information System

The paper, presents an approach to developing and running ETL processes implemented in Oracle Data Integrator (ODI), on the example of a hospital information system. Thanks to inversion of the classical order of ETL stages to Extract-Load-Transform (ELT) sequence, ODI simplifies and improves efficiency of most common ETL tasks. Several new features introduced in 12c version positively affects productivity, efficiency and functionality as well.

Performance Aspect of the In-Memory Databases Accessed via JDBC

The conception of storing and managing data directly in RAM appeared some time ago but in spite of very good efficiency, it was impossible to massive implementation because of hardware limitations. Currently, it is possible to store whole databases in memory as well as there are some mechanisms to organize pieces of data as in-memory databases. It has been the interesting issue how this type of databases behaves when accessing via JDBC. Hence we decided to test their performance in terms/sense of the time of SQL query execution. For this purpose TPC Benchmark\(^{\mathrm {TM}}\) H (TPC-H) was applied. In our research we focused on the open source systems such as Altibase, H2, HyperSQL, MariaDB, MySQL Memory.

The Classification of Music by the Genre Using the KNN Classifier

The article presents the possibility of classifying music tracks according to their musical genre. This issue is interesting because it is difficult to find solutions that look for similarity between songs based on their waveforms, as in this work. This article shows that such a classification is possible. For this process, the KNN classifier was used, for which it is possible to apply different metrics (metric spaces). The article shows the validity of testing different distance measures in the classification process. The analysis of music tracks and assignment to the appropriate genre is carried out, on the basis of attributes describing the music track. These attributes are obtained using the jAudio library. The development of further research in this area may allow finding other suitable music not only on the basis of historical data about the user (what he was listening to along with the music track) but also directly on the basis of the genre of the given song.