Filtry
wszystkich: 59
Wyniki wyszukiwania dla: K-NN
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How Specific Can We Be with k-NN Classifier?
PublikacjaThis paper discusses the possibility of designing a two stage classifier for large-scale hierarchical and multilabel text classification task, that will be a compromise between two common approaches to this task. First of it is called big-bang, where there is only one classifier that aims to do all the job at once. Top-down approach is the second popular option, in which at each node of categories’ hierarchy, there is a flat classifier...
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Selection of Relevant Features for Text Classification with K-NN
PublikacjaIn this paper, we describe five features selection techniques used for a text classification. An information gain, independent significance feature test, chi-squared test, odds ratio test, and frequency filtering have been compared according to the text benchmarks based on Wikipedia. For each method we present the results of classification quality obtained on the test datasets using K-NN based approach. A main advantage of evaluated...
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Improving css-KNN Classification Performance by Shifts in Training Data
PublikacjaThis paper presents a new approach to improve the performance of a css-k-NN classifier for categorization of text documents. The css-k-NN classifier (i.e., a threshold-based variation of a standard k-NN classifier we proposed in [1]) is a lazy-learning instance-based classifier. It does not have parameters associated with features and/or classes of objects, that would be optimized during off-line learning. In this paper we propose...
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Examining Feature Vector for Phoneme Recognition
PublikacjaThe aim of this paper is to analyze usability of descriptors coming from music information retrieval to the phoneme analysis. The case study presented consists in several steps. First, a short overview of parameters utilized in speech analysis is given. Then, a set of time and frequency domain-based parameters is selected and discussed in the context of stop consonant acoustical characteristics. A toolbox created for this purpose...
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Music Genre Recognition in the Rough Set-Based Environment
PublikacjaThe aim of this paper is to investigate music genre recognition in the rough set-based environment. Experiments involve a parameterized music data-base containing 1100 music excerpts. The database is divided into 11 classes cor-responding to music genres. Tests are conducted using the Rough Set Exploration System (RSES), a toolset for analyzing data with the use of methods based on the rough set theory. Classification effectiveness...
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Determination of authenticity of brand perfume using electronic nose prototypes
PublikacjaThe paper presents practical application of an electronic nose technique for fast and efficient discrimination between authentic and fake perfume samples. Two self-built electronic nose prototypes equipped with a set of semiconductor sensors were employed for that purpose. Additionally 10 volunteers took part in sensory analysis. The following perfumes and their fake counterparts were analysed: Dior – Fahrenheit, Eisenberg – J’ose,...
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Identyfikacja lotnych związków na podstawie odpowiedzi matryc czujników gazu
PublikacjaW pracy przedstawiono koncepcję systemu wykorzystującego wielowymiarową analizę danych, który służyć będzie do analizy odpowiedzi matrycy czujników gazu w celu identyfikacji lotnych związków występujących w powietrzu. Przedstawione podejście składa się z dwóch etapów. W pierwszym kroku wykonuje się proces kalibracji, polegający na utworzeniu w przestrzeni dwuwymiarowej grupy klas odpowiadających odpowiedziom czujników na konkretne...
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Identyfikacja lotnych związków na podstawie odpowiedzi matryc czujników gazów
PublikacjaW pracy przedstawiono koncepcję systemu analizy odpowiedzi matrycy czujników gazu wykorzystującą wielowymiarową analizę danych i prowadzącą do identyfikacji lotnych związków występujących w powietrzu. Przedstawione podejście składa się z dwóch etapów. W pierwszym kroku wykonuje się proces kalibracji, polegający na utworzeniu w przestrzeni dwuwymiarowej grupy klas odpowiadających odpowiedziom czujników na konkretne związki. Drugi...
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Mining Knowledge of Respiratory Rate Quantification and Abnormal Pattern Prediction
PublikacjaThe described application of granular computing is motivated because cardiovascular disease (CVD) remains a major killer globally. There is increasing evidence that abnormal respiratory patterns might contribute to the development and progression of CVD. Consequently, a method that would support a physician in respiratory pattern evaluation should be developed. Group decision-making, tri-way reasoning, and rough set–based analysis...
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Examining Feature Vector for Phoneme Recognition / Analiza parametrów w kontekście automatycznej klasyfikacji fonemów
PublikacjaThe aim of this paper is to analyze usability of descriptors coming from music information retrieval to the phoneme analysis. The case study presented consists in several steps. First, a short overview of parameters utilized in speech analysis is given. Then, a set of time and frequency domain-based parameters is selected and discussed in the context of stop consonant acoustical characteristics. A toolbox created for this purpose...
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Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning
PublikacjaThe aim of the study is to compare electroencephalographic (EEG) signal feature extraction methods in the context of the effectiveness of the classification of brain activities. For classification, electroencephalographic signals were obtained using an EEG device from 17 subjects in three mental states (relaxation, excitation, and solving logical task). Blind source separation employing independent component analysis (ICA) was...
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Rediscovering Automatic Detection of Stuttering and Its Subclasses through Machine Learning—The Impact of Changing Deep Model Architecture and Amount of Data in the Training Set
PublikacjaThis work deals with automatically detecting stuttering and its subclasses. An effective classification of stuttering along with its subclasses could find wide application in determining the severity of stuttering by speech therapists, preliminary patient diagnosis, and enabling communication with the previously mentioned voice assistants. The first part of this work provides an overview of examples of classical and deep learning...
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Discrimination of selected fungi species based on their odour profile using prototypes of electronic nose instruments
PublikacjaThe paper presents practical application of an electronic nose technique to fast and efficient discrimination of the samples of different fungi species such as: Penicillium chrysogenum, Cladosporium herbarum, Rhizopus oryzae, Alternaria alternata. Two prototypes of electronic nose instrument were utilized for investigation of discrimination capability with respect to odour profile of these fungi: the first prototype was based on...
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Employing Subjective Tests and Deep Learning for Discovering the Relationship between Personality Types and Preferred Music Genres
PublikacjaThe purpose of this research is two-fold: (a) to explore the relationship between the listeners’ personality trait, i.e., extraverts and introverts and their preferred music genres, and (b) to predict the personality trait of potential listeners on the basis of a musical excerpt by employing several classification algorithms. We assume that this may help match songs according to the listener’s personality in social music networks....
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Application of the neural networks for developing new parametrization of the Tersoff potential for carbon
PublikacjaPenta-graphene (PG) is a 2D carbon allotrope composed of a layer of pentagons having sp2- and sp3-bonded carbon atoms. A study carried out in 2018 has shown that the parameterization of the Tersoff potential proposed in 2005 by Ehrhart and Able (T05 potential) performs better than other potentials available for carbon, being able to reproduce structural and mechanical properties of the PG. In this work, we tried to improve the...
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Rezystancja uziemienia złącza kablowego SN
PublikacjaUdzielono odpowiedzi na pytanie czytelnika nadesłane do redakcji czasopisma INPE. Wyjaśniono zasady wyznaczania rezystancji uziemienia stacji elektroenergetycznej zawierającej transformator SN/nn. Wskazano prawidłowy tok postępowania w przypadku złącza SN zawierającego transformator SN/nn małej mocy zasilający urządzenia niskiego napięcia wyłącznie w obrębie tego złącza.
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Hybrid of Neural Networks and Hidden Markov Models as a modern approach to speech recognition systems
PublikacjaThe aim of this paper is to present a hybrid algorithm that combines the advantages ofartificial neural networks and hidden Markov models in speech recognition for control purpos-es. The scope of the paper includes review of currently used solutions, description and analysis of implementation of selected artificial neural network (NN) structures and hidden Markov mod-els (HMM). The main part of the paper consists of a description...
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Neural Network-Based Sequential Global Sensitivity Analysis Algorithm
PublikacjaPerforming global sensitivity analysis (GSA) can be challenging due to the combined effect of the high computational cost, but it is also essential for engineering decision making. To reduce this cost, surrogate modeling such as neural networks (NNs) are used to replace the expensive simulation model in the GSA process, which introduces the additional challenge of finding the minimum number of training data samples required to...
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Embedded device for indoor positioning of mobile terminals in ISM 2.4 GHz frequency band integrated with ESPAR antenna
PublikacjaIn the era of multifunctional mobile phones, wireless positioning is one of the most important branches of telecommunications development. This functionality is possible thanks to global positioning systems such as GPS, whose services are available to every average user. Global systems, however, suffer from their low accuracy in confined environments such as forests and building interiors. A popular...
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Performance improvement of NN based RTLS by customization of NN structure - heuristic approach
PublikacjaThe purpose of this research is to improve performance of the Hybrid Scene Analysis – Neural Network indoor localization algorithm applied in Real-time Locating System, RTLS. A properly customized structure of Neural Network and training algorithms for specific operating environment will enhance the system’s performance in terms of localization accuracy and precision. Due to nonlinearity and model complexity, a heuristic analysis...