two-class classification
Identification and Automatic ICA PSO Two Class Classification of Time Series RSN in Shaky Hand Syndrome
... for classification using ICA-PSO, two-class ...level two, 30 in- dependent components are obtained as 30 spatial maps using group ...2 class k means clustering is utilized on simulated ...
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A Corpus based Approach to Automatic Compound Extraction
... It uses n-gram mutual information, relative frequency count and parts of speech as the features for compound extraction.. The problem is modeled as a two-class classification problem bas[r] ...
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Efficient Altered Fingerprint Analysis and Rectification of Distorted Fingerprint
... label classification can give best feature. In positive classification, where the physical access control systems and user should negotiate for self- ...case classification broadly talks about low ...
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Acute kidney injury outcome in critically ill patients
... RIFLE classification was independent risk factors for mortality and mortality was highest among those in RIFLE class ...AKIN classification and RIFLE classification can predict mortality in ...
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SMOKE DETECTION BASED ON IMAGE PROCESSING BY USING GREY AND TRANSPARENCY FEATURES
... question classification is to define the classes of question or the types of ...in two stages; the first stage consists of Persian question sentences, which includes both coarse and fine grained category ...
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A New Class Based Associative Classification Algorithm
... associative classification, a new class based frequent pattern mining strategic is designed in CACA to cut down the searching space of frequent ...associative classification but help to guide the ...
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CLASS - A Study of methods for coarse phonetic classification
... were Training Training involves in data speech characteristics this work will systematically examining many to order each of be Feature extraction analysis 3 The Feature In data see info[r] ...
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Looking at the class associative classification training algorithm
... uncommon class labels in iterations that follow the initial ...only two classes and the frequency of one class is much higher than the other ...dominant class “negative”, which means that the ...
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Iot Botnet Detection Using System Call Graphs and One Class CNN Classification
... One-classSVM classification to detect malicious code on the Windows platform, based on features extracted from n-grams, reaching the above detection rate ...
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Vista ue at SemEval 2019 Task 5: Single Multilingual Hate Speech Detection Model
... For any text classification task, the most obvi- ous information to utilize is surface-level features, such as a bag of words. Indeed, unigrams and larger n-grams are included in the feature sets by a majority of ...
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An approach for correcting inhomogeneous atmospheric effects in remote sensing images
... Abstract. Two contextual-based approaches for correcting first order atmo- spheric effects due to atmospheric inhomogeneity and adjacency effect are ...noting classification accuracy on the basis that an ...
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Exploiting Class Label Frequencies for Text Classification
... Document classification is an example of Machine Learning (ML) in the form of Natural Language Processing ...document classification techniques a document is represented as a bag of words consisting of all ...
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Active Learning of Multi-Class Classification Models from Ordered Class Sets
... of two Million Song datasets (CD1 and CD2) (Bertin-Mahieux et ...or two classes indicating the genre that this song likely belongs ...The class label of each in- stance indicates the sentiment of ...
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One-class Classification: An Approach to Handle Class Imbalance in Multimodal Biometric Authentication
... the classification performance of the extremely imbalanced biometric data ...following two contributions have been ...impostor class, and thus, decreasing the degree of class imbalance and ...
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Dendogram-based SVM for Multi-Class Classification
... The goal of these experiments is to evaluate our method vs. “one-against-one”, “one-against- the other” and MLP ( Multi layer perceptron ) methods. The most important criterion in eval- uating the performance of these ...
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One-class classification of point patterns of extremes
... seizure is more costly than generating a false-positive classification for this type of seizure. Tables 2(a) and 2(b) show the mean performance scores calculated over the different test sets in the runs for three ...
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Multi class Animacy Classification with Semantic Features
... We also include a feature based on WordNet dis- tances. In this work, we use the path distance sim- ilarity measure provided in NLTK (Bird, 2006). In essence, this measure provides a score based on the shortest path that ...
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Classification of Imbalanced Data with a Geometric Digraph Family
... each class into clusters, and then, oversample the minority class or undersample the majority class proportional to each ...each class of gene expression data ...of class imbalance from ...
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OFF-LINE ARABIC HANDWRITTEN ISOLATED CHARACTER RECOGNITION
... By definition, features are the information extracted from the character image which is expected to represent the image shape. This information is mapped into a classifier for classification process [1]. In fact, ...
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Multi Class Classification Approach for Classification of ADAMs, MMPs and Their Subclasses
... Any two sequences with more then 90% sequence similarity were excluded from inclusion in the training data set since they can cause over training of the system ...
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