[PDF] Top 20 An Ensemble of Classifiers using Dynamic Method on Ambiguous Data
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An Ensemble of Classifiers using Dynamic Method on Ambiguous Data
... Ensemble is useful for several data mining applications like Intrusion Detection, Customer Relation Management (CRM), and Medical Image Classification etc. In many practical learning domains, there is large ... See full document
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A NEW SOFT SET BASED PRUNING ALGORITHM FOR ENSEMBLE METHOD
... of classifiers in the ensemble methods that produce the best prediction ...the ensemble classifiers is better than single ...of classifiers based on soft set ...full ensemble. ... See full document
8
Comprehensive benchmarking and ensemble approaches for metagenomic classifiers
... generated using a methodology described previously [37]. Briefly, six data- sets were created using the ART simulator with default error and quality base profiles [66] to simulate 100-bp Illu- mina ... See full document
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Melanoma Detection in Dermoscopic Images using Color Features
... the dynamic selection techniques used for classifier ...an ensemble of 15 decision stump trees are built using ...an ensemble of decision stump trees are built using bagging, the ... See full document
9
FCM BPSO: ENERGY EFFICIENT TASK BASED LOAD BALANCING IN CLOUD COMPUTING
... Ensemble classifiers or learners work by combining learners which are weak on their own nevertheless become very powerful when combined ...training data with replacement and then the output of each ... See full document
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Dynamic Weighted Majority: An Ensemble Method for Drifting Concepts
... With respect to complexity of the experts themselves, the STAGGER concepts consist of three attributes, each taking one of three possible values. Therefore, this implementation of weighted ma- jority maintained 27 ... See full document
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Ensemble of Classifiers Based on Association Rule Mining
... in data mining that utilizes the association rule discovery techniques to build classification systems, also known as associative ...classifiers. Ensemble methods have been called the most powerful ... See full document
5
An Ensemble of Classifiers using Weighted Instance Selection
... years data are rapidly growing in size, there is difficult task for storing these data in well ...huge data is used for discovering the hidden knowledge that is termed as Data ...mining. ... See full document
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Ensemble of Decision Tree Classifiers for Mining Web Data Streams
... manipulates data to accomplish something, such as storing ...retrieving data from the model necessary to generate the response, and provides HTML forms to permit user ...form data, updates the model ... See full document
7
Resample-based Ensemble Framework for Drifting Imbalanced Data Streams
... resample-based ensemble framework for a drifting data stream with class imbalance ...novel ensemble framework that includes a long- term static classifier and multiple dynamic ... See full document
12
Classifying Unstructured Text Using Structured Training Instances and an Ensemble of Classifiers
... The classifiers were im- plemented using the well-known WEKA framework for machine learning and data mining ...TVs. Data were obtained using live commercial websites, namely Argos (190 ... See full document
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Object detection using ensemble of linear classifiers with fuzzy adaptive boosting
... misclassified data in the previous stage would be correctly classified by a next fea- ...new method that can improve the accuracy and performance of the Adaboost algorithm by providing the way of assigning ... See full document
10
Classifier Ensemble Framework: a Diversity Based Approach
... a method based on which the best classifier is detected for any arbitrary problem, and thanks to significant improvement in accuracy, researchers turn to ensemble methods in almost every task of pattern ... See full document
10
Shape-Based Single Object Classification Using Ensemble Method Classifiers
... Detection includes the detection of position and other characteristics of the moving object image obtained from camera and in the extraction, the detected object estimated the trajectory of the object in the image plane. ... See full document
6
CSIRO Data61 at the WNUT Geo Shared Task
... use ensemble methods to cap- italise on four component methods: heuristics based on metadata, a label propagation method, timezone text classifiers, and an information retrieval ... See full document
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Performance Analysis of Automobile data using Bagged Ensemble Classifiers
... training data set, which is a set of past examples in which the values of the target variable are ...common data mining ...performing method for a specific ...of using a single supervised ... See full document
9
Improving Classification Accuracy through Ensemble Technique in Data Mining Bhavesh Patankar *1 , Dr. Vijay Chavda 2
... individual classifiers that make them ...by using a single learning base classifier, such as ...Various classifiers are created by changing the training set (as done in boosting or bagging), changing ... See full document
5
Predicting age from the transcriptome of human dermal fibroblasts
... the ensemble method so effective at predicting age from gene expression in fibroblasts? A necessary and sufficient condition for an ensemble to be more accurate than any of its individual ... See full document
8
Using Multitier Ensemble Classifiers for Organizing Multimedia Big Data - An Visualization
... LIME classifiers originating as a contribution to the general approach considered by many ...LIME classifiers can be used to achieve further improvement of the classification ...diverse ensemble meta ... See full document
5
Context awareness computing in smart spaces using stochastic analysis of sensor data
... For this purpose, we built statistic models of an actual dataset that apply a Bayesian network. The Bayesian network enables to calculate join probability distribution on the entire dataset by using CPT. If the ... See full document
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