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.
Most of graph-based methods for semi-supervised learning are transductive, giving predictions for only the unlabeled data in the training set, and not for an arbitrary test point. SLC (Semi-supervised Local Linear Coordinate), which is based on LLC (Local Linear Coordinate) is present here as an inductive method. The mixture of factor analyzers is used to model the raw data set, and the label smoothness...
Network security is becoming an increasingly important issue, since the rapid development of the Internet. Network Intrusion Detection System (IDS), as the main security defending technique, is widely used against such malicious attacks. Data mining and machine learning technology has been extensively applied in network intrusion detection and prevention systems by discovering user behavior patterns...
In this paper, we present fast algorithms on mining coevolving time series, with or with out missing values. Our algorithms could mine meaningful patterns effectively and efficiently. With those patterns, our algorithms can do forecasting, compression, and segmentation. Furthermore, we apply our algorithm to solve practical problems including occlusions in motion capture, and generating natural human...
Gaussian mixture model (GMM) has been widely used in fields of image processing and investment data mining. However, in many practical applications, the number of the components is not known. This paper proposes a kind of greedy merge EM (GMEM) learning algorithm such that the number of Gaussians can be determined automatically with the minimum message length (MML) criterion. Moreover, the greedy...
Intrusion Detection System (IDS) has recently emerged as an important component for enhancing information system security. Data mining and machine learning technology has been extensively applied in network intrusion detection and prevention systems by discovering user behavior patterns from the network traffic data. In this paper, we propose a novel signature searching to detect intrusion based on...
In this paper, an improved fuzzy membership function determination is proposed to train the fuzzy support vector machine (FSVM) for classification which the sample set in reality environment is increasing, and it often contains a lot of noise and outliers. In the improved algorithm, the sample points have the different types of memberships in different regions. The dual membership is introduced to...
To improve the training speed of SVM, we propose a new SVM training approach which takes thick convex-hull as training set. The approach makes better use of the margin information for classification of data sets, and thus extends the use of convex hull to approximately linearly separable problems. Experiments on 5 UCI data sets indicate that the approach speeds up training of SVM with guarantee of...
Entity relation extraction (RE) is an very important research domain in information extraction, we can regard RE as a classification problem in this paper, RE is still original study field in Chinese language now, maximum entropy (ME)-based machine learning is the first time to be used to extract entity relations between named entities from Chinese texts, Thirteen features have been designed for entity...
In this paper a novel flexible kernel independent component analysis (FKICA) algorithm is defined and its local stability on feature space is discussed. In the FKICA algorithm, the shape of nonlinear activation function in the learning algorithm varies depending on the Gaussian exponent, which is properly selected according to the kurtosis of estimated source in feature space. In the framework of...
Support vector machine (SVM) is a kind of machine learning method based on statistical learning theory, which has become the hotspot of machine learning research. In the paper we discuss the application research of the SVM in communication such as multi-user detector in 3 rd CDMA technology, image processing and speech identification. In the conclusion section, we elicit the advantage and the shortcoming...
Podaj zakres dat dla filtrowania wyświetlonych wyników. Możesz podać datę początkową, końcową lub obie daty. Daty możesz wpisać ręcznie lub wybrać za pomocą kalendarza.