Using the meta-classifier
Simultaneous meta-data and meta-classifier selection in multiple classifier system.
... simultaneous meta-data and meta-classifier selection method for ensemble ...generate meta-data as the predictions of base ...of meta-data and meta-classifier for the ...of ...
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Improving a SVM Meta-classifier for Text Documents by using Naive Bayes
... modified meta-classifier with 9 classifiers based on Euclidian distance were ...modified meta-classifier which achieved only ...the meta- classifier with 8 SVM type classifiers ...
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Analyzing Cervical Cancer by using an Ensemble Learning Approach based on Meta Classifier
... of using the model. After data preprocessing, we have used many meta classifier algorithms to analyze these ...). Using these classifiers, we have found the MALE (Mean Absolute Logarithmic ...
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MAZA at SemEval 2016 Task 11: Detecting Lexical Complexity Using a Decision Stump Meta Classifier
... a meta-classifier ...a meta-classifier for our entry, also re- ferred to as classifier ...A meta-classifier ar- chitecture is generally composed of an ensemble of base ...
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An Efficient Meta Classifier Technique For Membranous Nephropathy Kidney Disease
... technique meta classifier to predict the disease so that the necessary action can be taken to save the life of a ...program meta classifier is employed in our work to predict the ...
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Differential Evolution Based Optimization of SVM Parameters for Meta Classifier Design
... Proposed Meta Classifier Approach SVM is relatively a new member in the family of classification and regression techniques which origi- nated from statistical learning theory ...
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Component-wise analysis of metaheuristic algorithms for novel fuzzy-meta classifier
... this, ANFIS is incorporated with other techniques such as clustering methods (Cai, 2017), support vector machine (Azadeh et al., 2013) to generate smaller number of rules; on the other hand, ANFIS architecture has also ...
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Ensemble Meta Classifier with Sampling and Feature Selection for Data with Multiclass Imbalance Problem
... hybrid classifier was carried out using Weka, a well-known machine learning tool that can be customised to create a new classifier ...experimented using machine learning packages to find the ...
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Language Identification using Classifier Ensembles
... aggregated using a fusion ...on meta-learning may employ a stacked architecture where the output from a first set of classifiers is fed into a second level meta-classifier and so ...
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A meta stacked ensemble probabilistic classifier
... algorithm; Decision tree; NER; Mongo DB; Neo4j; GraphDB. The data was collected from different websites,blogs and classified using Naive Bayes related to vandalism, murder, robbery, burglary, sex abuse, gang rape ...
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Establishing Correspondences between Attribute Spaces and Complex Concept Spaces Using Meta-PGN Classifier
... Abstract. In this paper, we present one approach for extending the learning set of a classification algorithm with additional metadata. It is used as a base for giving appropriate names to found regularities. The ...
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Security Of Big Data Using Multitier Classifier
... LIME classifier is large because it is tailored for handling big ...This classifier is also concern for security of big ...ensemble Meta classifiers. The ensemble meta classifiers into several ...
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Meta-analysis of transcriptome data identifies a novel 5-gene pancreatic adenocarcinoma classifier
... is meta-analysis of multiple transcriptional profiling studies applying identical analytics that can generate gene signatures with increased reproducibility and sensitivity, revealing biological insight not ...
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A Meta-Stacked Software Bug Prognosticator Classifier
... 2 Department of CSE, Aurora’s Technological and Research Institute, Uppal, Hyderabad, Telangana, India ABSTRACT Predicting defects defines the proactive process of classifying the defects that can be found in entire ...
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Detection of Rice Disease Using Bayes Classifier and Minimum Distance Classifier
... effective classifier as compare to SVM and it would reduce the computational cost, they also proved that KNN has high accuracy rate as compare to ...by using SURF (Speed Up Robust Feature) ...
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Chinese Classifier Assignment Using SVMs
... {huguo, huayan}@cs.sunysb.edu Abstract In Chinese, nouns need numeral clas- sifiers to express quantity. In this pa- per, we explore the relationship be- tween classifiers and nouns. We ex- tract a set of lexical, ...
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Identifying Concept Attributes Using a Classifier
... and k is the number of clusters. 7 Discussion and Conclusions The lexicon does not simply contain information about synonymy and hyponymy relations; it also contains information about the attributes of the concepts ...
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Using A* for Inference in Probabilistic Classifier Chains
... {deiner,quevedo,elena,juanjo}@aic.uniovi.es, [email protected] Abstract Probabilistic Classifiers Chains (PCC) offers in- teresting properties to solve multi-label classifica- tion tasks due to its ability to ...
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Sentiment Analysis using Ensemble Classifier
... Ensemble Classifier: In practice, classifiers are built to classify unseen data, usually referred to as a target ...a classifier ensemble is formed by the majority voting of the class obtained by each ...
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Classifier Selection using the Predicate Depth
... This motivates us to study the problem of selecting the best hypothesis, given the posterior belief. The goal is to select a hypothesis that will generalize well. Two well known methods for achieving this are the Bayes ...
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