hybrid classifier
Diabetic Retinopathy Detection using Hybrid Classifier
... Abstract: Diabetic Retinopathy is one of the leading causes for blindness in today’s working age population. Patients suffering from Diabetes Mellitus are prone to Diabetic Retinopathy. Diabetic Retinopathy is a ...
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Face Recognition based Automated Attendance Management System using Hybrid Classifier
... new hybrid classifier based AAMS helps to put attendance of the student when the face is recognized using surveillance camera as shown in the Fig- ...
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Ecg Signal based Arrhythmia Detection System using Optimized Hybrid Classifier
... ECG signal detection is associated with cardiac analysis and diagnosis. It can be indicated as an iteration of P-QRS-T waves. The main objective behind ECG signal analysis is to discover the QRS complex. R peak detection ...
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Heart Disease Prediction Method using Hybrid Classifier
... the classifier that is designed in this research work is hybrid ...The hybrid classifier is combination of random forest and decision tree ...forest classifier is applied for the ...
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Hybrid Classifier for Sentiment Analysis using Effective Pipelining
... a hybrid method for analyzing ...based classifier where a tweet after undergoing preprocessing is first classified by the lexicon and the rules classifier and is sent to the machine learning module ...
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Design Of Hybrid Classifier For Prediction Of Diabetes Through Feature Relevance Analysis
... The classifier selects the most relevant features that contribute more towards the prediction of the ...of classifier being used. Classifier evaluation is done to optimize the classifier with ...
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Hybrid Classifier for gait recognition
... K-Nearest Neighbours (KNN) classifier instantly finds the data set on the basis of Euclidian distance. In case of K-NN first the data is trained and stored in memory. Recognition is performed on a tested sample by ...
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Hybrid classifier for fault location in active distribution networks
... Following the occurrence of a short circuit fault in a dis- tribution network, the restoration process may take from tens of minutes to hours to complete. During fault man- agement, fault location (FL) can serve as an ...
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A Hybrid Classifier for Classification of Rice Crop Varieties
... In Asia the most important staple food is Rice (Oryza sativa L.), and it has a lot of remote-sensing-based research on single biotic stress and infection levels, including panicle blast (13), leaf blast (14), leaf brown ...
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Hybrid SVM-ANN Classifier is used for Heart Disease Prediction System
... This hybrid classifier has been performed in the coronary heart disease (CHD) risk assessment problem and the experimental results are explained and ...
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Anomaly Intrusion Detection based on a Hybrid Classification Algorithm (GSVM)
... a hybrid classifier is designed based on a combination of the GSA and SVM ...GSVM classifier is to optimize the accuracy of the SVM classifier by detecting the subset of the best values of the ...
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Hybrid Multimodal Evolution Dense Support Vector Machine based classification for Parkinson’s disease diagnosis
... new hybrid algorithm. For that, the proposed work utilizes a new hybrid classification algorithm named as Hybrid Multimodal Evolution Dense Support Vector Machine (HMEDSVM) classification algorithm ...
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Automatic Leaf Disease Detection and Classification using Hybrid Features and Supervised Classifier
... SVM classifier is used to detect and classify early scorch, yellow spots, brown spots, late scorch with efficiency of ...the classifier which is not that efficient in classifying the disease but effectively ...
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1. A hybrid e-mail spam filtering technique using data mining approach
... Abstract - Communication is a primary need of human beings therefore new techniques are invented to support low cost, efficient and adoptable techniques for new generation communication technology. SMS and email messages ...
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E Payment and Transactions using QR Codes
... [80] G. M. Jaradat, A. Al-Badareen, M. Ayob, M. Al-Smadi, I. Al-Marashdeh, M. Ash-Shuqran, And E. Al-Odat, "Hybrid Elitist- Ant System For Nurse-Rostering Problem," Journal Of King Saud University-Computer ...
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Developing and Implementing a Barcode based Student Attendance System
... [37] G. M. Jaradat, A. Al-Badareen, M. Ayob, M. Al-Smadi, I. Al-Marashdeh, M. Ash-Shuqran, and E. Al-Odat, "Hybrid Elitist- Ant System for Nurse-Rostering Problem," Journal of King Saud University-Computer ...
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Hybrid radar emitter recognition based on rough k-means classifier and SVM
... the radar emitter signal include a radio frequency (RF), a pulse repeating frequency (PRF), antenna rotate rate (ARR) and a pulse width (PW). 240 groups of data are gen- erated on above original radar information for ...
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Model Combination for Correcting Preposition Selection Errors
... Much of the previous work has used well-formed text when training contextual classifiers due to the lack of large error-annotated corpora. Han et al. (2010) conducted experiments with a relatively small error-annotated ...
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Sentiment Analysis of Tweets using Sentiment Features
... 3. Hybrid Methods: Hybrid method undertakes a combination of each of the above mentioned classes to perform opinion mining ...learning classifier. Hybrid method would resolve many of the major ...
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Jstacs: A Java Framework for Statistical Analysis and Classification of Biological Sequences
... a classifier, chooses a learning principle for learning the parameters of this classifier, and learns this classifier on training ...the classifier for predicting class labels for previously ...
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