Serwis Infona wykorzystuje pliki cookies (ciasteczka). Są to wartości tekstowe, zapamiętywane przez przeglądarkę na urządzeniu użytkownika. Nasz serwis ma dostęp do tych wartości oraz wykorzystuje je do zapamiętania danych dotyczących użytkownika, takich jak np. ustawienia (typu widok ekranu, wybór języka interfejsu), zapamiętanie zalogowania. Korzystanie z serwisu Infona oznacza zgodę na zapis informacji i ich wykorzystanie dla celów korzytania z serwisu. Więcej informacji można znaleźć w Polityce prywatności oraz Regulaminie serwisu. Zamknięcie tego okienka potwierdza zapoznanie się z informacją o plikach cookies, akceptację polityki prywatności i regulaminu oraz sposobu wykorzystywania plików cookies w serwisie. Możesz zmienić ustawienia obsługi cookies w swojej przeglądarce.
Fuzzy C-Means (FCM) is the most popular algorithm of the fuzzy clustering approach. Although FCM and its variations have shown good performance in cluster detection, they do not consider that different variables could produce different membership degrees. Motivated by this, the Multi-variate Fuzzy C-Means (MFCM) method was proposed. The MFCM computes membership degrees of both clusters and variables...
Recent advances in cluster analysis highlight the importance of finding multiple meaningful partitions and point out to the need for approaches to evaluate them. They also suggest that the evaluation should consider knowledge of a domain expert. In this paper, we present a visualization method, called PVis1 (Partition's Visualizer), that allows the integrated visualization of a collection of partitions...
Supervised learning methods have been successfully used to build classifiers for the identification of promoter regions. The classifier is often built from a dataset that has examples of promoter (positive) and non-promoter (negative) regions. Thus, a careful selection of the data used for constructing and evaluating a promoter finding algorithm is a very important issue. In this context, experimentally...
In previous works, it was proved that General Single-layer Sequential Weightless Neural Networks (GSSWNNs) are equivalent to probabilistic automata. The class of GSSWNNs is an important representative of the research on temporal pattern processing in Weightless Neural Networks or RAM-based neural networks. Some of the proofs provide an algorithm to map any probabilistic automaton into a GSSWNN. They...
Machine Learning algorithms have been widely used for gene expression data classification, despite the fact that these data have often intrinsic limitations, such as high dimensionality and a small number of examples. Few studies try to characterize to which extent these aspects can influence the performance of the classification models induced. In this paper we compute different measures characterizing...
Ensemble of classifiers is an effective way of improving performance of individual classifiers. However, the choice of the ensemble members can become a very difficult task, in which, in some cases, it can lead to ensembles with no performance improvement. In order to avoid this situation, there is a need to find effective classifier member selection methods. In this paper, a DCS (Dynamic Classifier...
Podaj zakres dat dla filtrowania wyświetlonych wyników. Możesz podać datę początkową, końcową lub obie daty. Daty możesz wpisać ręcznie lub wybrać za pomocą kalendarza.