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Showing 1 to 5 of 5 for “"two-class classification"”.

  1. Fault detection and diagnostics of an HVAC sub-system using adaptive resonance theory neural networks

    … rule-based expressions, regression, one-class support vector machine (SVM), back-propagation, adaptive resonance theory (ART), and lateral priming adaptive resonance theory (LAPART). The diagnosis of AHU faults were performed using a multi-class SVM and LAPART algorithms. The results from …

    unm Repository record for Fault detection and diagnostics of an HVAC sub-system using adaptive resonance theory neural networks (opens in a new tab)

  2. The Influence of Scoring Parameters on Precision-Based AdaBoost

    Many problems in data science involve classification, i.e., dividing a dataset into dif- ferent predefined classes. Such classification problems are often solved with machine learning techniques. Using a combination of classifiers in an ensemble is an effective method to improve the accuracy of the …

    regina Repository record for The Influence of Scoring Parameters on Precision-Based AdaBoost (opens in a new tab)

  3. Some Advances in Classifying and Modeling Complex Data

    In statistical methodology of analyzing data, two of the most commonly used techniques are classification and regression modeling. As scientific technology progresses rapidly, complex data often occurs and requires novel classification and regression modeling methodologies according to the data …

    vt Repository record for Some Advances in Classifying and Modeling Complex Data (opens in a new tab)

  4. EEG Feature Extraction and Pattern Recognition Based on Chaotic Systems

    … a novel extension of ANN(Artificial Neural Networks) based modelling for chaotic systems. The Rossler’s and Chua’s systems are used for the study. A NARX (Nonlinear Autoregressive Exogenous) model is proposed to train bifurcation patterns of chaotic systems and performance of various NARX …

    regina Repository record for EEG Feature Extraction and Pattern Recognition Based on Chaotic Systems (opens in a new tab)

  5. Eye detection using discriminatory features and an efficient support vector machine

    … detection. This dissertation further proposes two discriminatory feature extraction (DFE) methods for eye detection. The first DFE method, discriminant component analysis (DCA), improves upon the popular principal component analysis (PCA) method. The PCA method can derive the optimal features …

    njit Repository record for Eye detection using discriminatory features and an efficient support vector machine (opens in a new tab)