binary classifier
Binary classifier metrics for optimizing HEP event selection
... a binary classifier is generally used by choosing a specific operating point, and in this case what counts is which ROC provides the better performance in the region where the operating point is chosen ...
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Support Vector Machine Neural Network Based Optimal Binary Classifier for Diabetic Retinopathy
... ABSTRACT: This paper explores the neural network as optimal binary classifier for diabetic retinopathy. Diabetic retinopathy is an eye syndrome caused by the impediment of diabetes and it can be detected ...
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An RNN based Binary Classifier for the Story Cloze Test
... with binary labels of 1 for correct endings (positive ex- amples) and 0 for incorrect endings (negative ex- ...a binary classifier to distinguish between these positive and negative ...
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Empirical Analysis of a Quantum Classifier Implemented on IBM’s 5Q Quantum Computer
... This classifier was tested on iris dataset and a circles data ...quantum classifier if some visualization of its working can be ...quantum binary classifier to a multiclass classifier, ...
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Revision Learning and its Application to Part of Speech Tagging
... a binary classifier with higher capacity to revise the errors made by the stochastic model with lower capacity as fol- lows: During the training phase, a ranking is assigned to each class by the stochastic ...
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Permuted and Augmented Stick-Breaking Bayesian Multinomial Regression
... stick-specific binary random variables that are mu- tually independent given their covariate-dependent stick success probabilities, which are parameterized by the regression coefficients of their corresponding ...
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Fault Classification of Reciprocating Compressor Based on Neural Networks and Support Vector Machines
... a binary classifier it compares only two things at a time ...the classifier feature selection and extraction should be limited to those features useful for classification [4- ...
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EMG DIAGNOSIS VIA TIME DOMAIN FEATURES AND BINARY SUPPORT VECTOR MACHINE CLASSIFICATION
... integrated binary classifier based on SVM is adopted in clinical electromyography for differentiating neuromuscular ...the binary SVM classifier can be effectively trained for MUAPs ...
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Classification of regional land cover in ALOS PALSAR’s FBD data based on support vector machines
... 1) Binary Classifier: In the framework of this paper, 50-m mosaic PALSAR products are only used, restricting the features to be the backscattering coefficients plus some textural ...
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Hierarchical Transfer Learning for Multi label Text Classification
... a binary classifier for ...C1 binary classi- fier with the final model parameters of P1 classi- ...C1 classifier, the C12 clas- sifier is initialized with parameters from C1 and so ...parent ...
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Sign language recognition with multi feature fusion and Adaboost classifier
... the classifier with HOG (Histogram of oriented Gradients), SIFT (Scale Invariant Feature Transform) and SURF (Speeded Up Robust Features) with Adaboost ...drop-in classifier performance can be attributed to ...
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A Binary Neural Decision Table Classifier
... a binary associative-memory neural network. We demonstrate how the binary associative-memory neural network can form the decision table index to map between attribute values and data ...the binary ...
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Learning subjective nouns using extraction pattern bootstrapping
... Bayes classifier that uses the WBO features, which performed well in prior research on sentence-level subjectivity classification (Wiebe et ...Bayes classifier that uses unigram bag-of- words features, with ...
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Liveness Detection Technique for Prevention of Spoof Attack in Face Recognition System
... The developed system identifies the user being genuine or not, in face biometric security systems. The proposed system is implemented by integrating standard algorithm like Voila Jones algorithm for face detection, LBP ...
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LOAD CURRENT CONTROL BASED ON LUENBERGER OBSERVER FOR THREE PHASE POWER CONVERTER SVPWM
... A new approach has been proposed for the automatic modulation classification of IF ASK\FSK\PSK signals at low SNR. It is based on mean-filter de-noising, instantaneous features and binary tree classifier. ...
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Margin Trees for High-dimensional Classification
... two-class classifier (“one-versus-all” and “one-versus one’ or “all pairs’), and others modifying the support vector loss function to deal directly with more than two classes (Weston and Watkins, 1999; Lee et ...a ...
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Automated System for Detection of High Risk Diabetic Macular Edema in Color Retinal Images
... The binary classification of Stage 0 (Normal) and Stage 2 (High Risk Diabetic Macular Edema) was performed on dataset from MESSIDOR database, and the SVM classifier with RBF kernel obtained highest accuracy ...
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Tanimoto Based Similarity Measure for Intrusion Detection System
... In this paper we introduced Tanimoto based similarity measure for host-based intrusions using binary feature set for training and classification. The k-nearest neighbor (kNN) classifier has been utilized to ...
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Feature vector of binary image using Freeman Chain Code (FCC) representation based on structural classifier
... for binary image: chain code based and run-length based algorithms ...a binary image as input. Binary image is a representation with only two possible gray values for each pixel, such as “0” and ...
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Event recognition on images using support vector machine and Multi Level Histograms of local patterns
... Local Binary Pattern and Local Derivative Pattern) and support vector machine ...best classifier in terms of AUC metric is "Liblinear" with local binary ...
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