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Nonparametric estimation and inference for polytomous discrimination index
Statistical Methods in Medical Research, 2017Polytomous discrimination index is a novel and important diagnostic accuracy measure for multi-category classification. After reconstructing its probabilistic definition, we propose a nonparametric approach to the estimation of polytomous discrimination index based on an empirical sample of biomarker values.
Jialiang, Li +4 more
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Learning Locality Discriminating Indexing for Text Categorization
Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007), 2007This paper introduces a locality discriminating indexing (LDI) algorithm for text categorization. The LDI algorithm offers a manifold way of discriminant analysis. Based on the hypothesis that samples from different classes reside in class-specific manifold structures, the algorithm depicts the manifold structures by a nearest-native graph and a ...
Jiani Hu +3 more
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Fuzzy Similarity Index For Discrimination Of EEG Signals
2006 International Conference of the IEEE Engineering in Medicine and Biology Society, 2006In this study, a new approach based on the computation of fuzzy similarity index was presented for discrimination of electroencephalogram (EEG) signals. The EEG, a highly complex signal, is one of the most common sources of information used to study brain function and neurological disorders.
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The Discriminative Validity of the Whitaker Index of Schizophrenic Thinking
Journal of Personality Assessment, 1978An attempt was made to assess the discriminative validity of the WIST with a sample of psychiatric inpatients. Through the use of a standardized structured interview and a diagnostic system for schizophrenia based on the use of discriminant function analysis with nonpathognomic symptom combinations, a reliable and valid system was used to establish the
C S, Newmark, M, Simpson, T, Jones
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Palmprint recognition via discriminative index learning
2016 23rd International Conference on Pattern Recognition (ICPR), 2016In the past years, deep convolutional neural networks (CNNs) have become extremely popular in the computer vision and pattern recognition community. The computational power of modern processors, efficient stochastic optimization algorithms, and large amounts of training data allowed training complex tasks-specific features directly from the data in an ...
Jan Svoboda +2 more
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The visual N1 component as an index of a discrimination process
Psychophysiology, 2000Many previous studies have demonstrated that the visual N1 component is larger for attended‐location stimuli than for unattended‐location stimuli. This difference is observed typically only for tasks involving a discrimination of the attended‐location stimuli, suggesting that the N1 wave reflects a discrimination process that is applied to the attended
E K, Vogel, S J, Luck
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Speech and Singing Discrimination for Audio Data Indexing
2014 IEEE International Congress on Big Data, 2014This study investigates the technique of automatically discriminating speech from singing voices for audio data indexing. We propose a discrimination system based on both timbre and pitch feature analyses. In using timbre features, voice recordings are converted into Mel-Frequency Cepstral Coefficients and their first derivatives and then analyzed ...
Wei-Ho Tsai, Cin-Hao Ma
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The risk of malignancy index in discrimination of adnexal masses
International Journal of Gynecology & Obstetrics, 2007To assess the ability of the risk of malignancy index (RMI) based on a serum CA125 level, ultrasound findings and menopausal status, to discriminate benign from malignant adnexal masses.Between September 2002 and November 2004, 296 women with adnexal masses were enrolled. The sensitivity, specificity, positive (PPV) and negative predictive values (NPV)
S, Ulusoy +5 more
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Feature Selection Based on Neighborhood Discrimination Index
IEEE Transactions on Neural Networks and Learning Systems, 2017Feature selection is viewed as an important preprocessing step for pattern recognition, machine learning, and data mining. Neighborhood is one of the most important concepts in classification learning and can be used to distinguish samples with different decisions.
Changzhong Wang +5 more
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Experiments with discrimination-tree indexing and path indexing for term retrieval
Journal of Automated Reasoning, 1992zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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