Base Classifier
Title: Supremacy of Rotation Forest with LMT Base Classifier in Prediction of Phishing Websites
... Abstract: Phishing is the skill of publishing a website of a credible organisation with the aim to acquire user‟s secretive data such as bank account detail, usernames, passwords and many more personal information. ...
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Performance Behavior of Intrusion Detection System (Ids) Based On Ensemble Base Classifier (EBC)
... The planned hybrid classifier produces best results using the features of hybrid methods. Also, the performance of proposed method is compared with traditional classifiers: Nave Bayes N B, Support Vector Machine ...
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Semi-Supervised Learning Based Prediction of Musculoskeletal Disorder Risk
... Recently, studies suggest that it is beneficial to use semi-supervised classification approach in situations where number of labeled data are sparse. The goal of semi-supervised classification is to use un-labeled data ...
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BrainEE at SemEval 2019 Task 3: Ensembling Linear Classifiers for Emotion Prediction
... A simple way of combining the base-classifiers is to take the average of their weights after train- ing. A more common approach is to exploit the output activations using different techniques. In (Xia et al., ...
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Design of Ensemble Classifier Selection Framework Based on Ant Colony Optimization for Sentiment Analysis and Opinion Mining
... ensemble classifier selection framework which is based on Ant Colony Optimization and provides ensemble classifiers with best ...of base classifiers and dataset as ...individual base ...
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eRFSVM: a hybrid classifier to predict enhancers-integrating random forests with support vector machines
... hybrid classifier called eRFSVM in this study, using random forests as a base classifier, and support vector machines as a main ...The base classifier trained datasets from a single ...
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Survey on Method of Drift Detection and Classification for time varying data set
... efficient classifier to define concept drift and classify data examples ...the base classifier was not able to learn the old concept well and thus there is need of completely new classifier is ...
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GLOBAL JOURNAL OF ADVANCED ENGINEERING TECHNOLOGIES AND SCIENCES RECOGNITION OF PERSIAN HANDWRITTEN NUMBERS BASED ON ASSEMBLY OF REINFORCED CLASSIFIERS Hamid Parvin*, Seyed Ahad Zolfagharifar, Faramarz Karamizadeh
... three classifier decision trees, neural networks and 3 nearest neighbor has been ...of base 3-near-the neighbor classifier in the proposed methods is not so much ...proposed classifier by ...
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SPECTRUM INVESTIGATION FOR SHARING ANALYSIS BETWEEN BWA SYSTEM AND FSS RECEIVER
... it in our proposed methodology. Diversity as one of the most important factors used in the construction of ensemble is achieved through four ways, which are: using different subsets of training data, different subsets of ...
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Multiple prediction combination and confidence measures for marine object detection
... subsetting classifier with a given base classifier may be considered to succeed if it is more accurate than a single classifier with the same type and settings: that is, if it improves ...
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Predicting Primary Tumors using Multiclass Classifier Approach of Data Mining
... a base classifier in multiclass classifier approach along with oversampling technique SMOTE and Random forest as a binary classifier on various parameters using primary tumor dataset ...
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On Support Vector Machine Ensembles for Classification of Recombination Breakpoint Regions in Saccharomyces Cerevisiae
... We used nucleotide compositional features (see Methods section for details) as the input for the classification. Performances of models were evaluated on tenfold cross- validation. We have used Support Vector Machine ...
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Adapting Self Training for Semantic Role Labeling
... Self-training (Yarowsky, 1995) is a semi- supervised algorithm which has been well stu- died in the NLP area and gained promising re- sult. It iteratively extend its training set by labe- ling the unlabeled data using a ...
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Performance Analysis of Automobile data using Bagged Ensemble Classifiers
... bagging classifier in conjunction with radial basis function and support vector machine as the base learner and the performance comparison has been demonstrated using Auto Imports and Car Evaluation ...
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Inducing a Lexicon of Abusive Words – a Feature Based Approach
... We examined the task of inducing a lexicon of abusive words. We presented novel features in- cluding surface patterns, sentiment views, polar intensity and general purpose lexical resources, particularly Wiktionary. The ...
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A Survey On Investigation Of Students Placement Log Using Machine Learning Algorithms
... perceptron classifier that has found as the more promising one, which assured the highest true positive and false positive rate as 77%, 89%, ...perceptron classifier have shown in figure ...
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Stylistic analysis and recognition of piano sonatas of four composers -- Mozart, Chopin, Debussy, Anton Webern
... the matching, of knowledge base for base and "knowledge" between characteristics characteristics a characteristics classifier the into characteristics the the comparisons musical for sty[r] ...
102
INTERACTING THROUGH DISCLOSING: PEER INTERACTION PATTERNS BASED ON SELF DISCLOSURE LEVELS VIA FACEBOOK
... (13) We make a comparison between our proposed framework with have used similar experimental setups and dataset to achieve the fairness principle. The obtained results have been compared with [30, 31] to measure the ...
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Coastline carrying capacity monitoring and assessment based on GF-1 satellite remote sensing images
... This paper employed object-oriented classification to extract coastline from GF-1 satellite remote sensing im- ages. First, the GF-1 images were divided into segmenta- tion in suitable scale. Scale segmentation divided ...
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Enterprise Credit Risk Evaluation models: A Review of Current Research Trends
... case base reasoning, Support vector machine, bayesian classifier, and fuzzy rule based classifier will have to be seamlessly integrated, implemented, tested and ...
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