[PDF] Top 20 Classifier Ensemble Framework: a Diversity Based Approach
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Classifier Ensemble Framework: a Diversity Based Approach
... an ensemble approach that uses a decision tree as its primary ...trained classifier is increased, whereas that of the correctly predicted ones is ... See full document
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An Intelligent Model for Online Recruitment Fraud Detection
... ble approach based on Random forest classifier to detect Online Recruitment Fraud ...detection, ensemble classifier using Random Forest is ... See full document
22
Swarm based classifier model using ensemble feature ranking methods
... an ensemble feature ranking technique. The ensemble approach determines a feature’s importance or score from multiple feature ranking techniques which are combined to generate three ranking lists: ... See full document
8
Analyzing Cervical Cancer by using an Ensemble Learning Approach based on Meta Classifier
... Feature selection is an important part in the field of data analy- sis. It help us to create an accurate predictive model by remov- ing unneeded, irrelevant and redundant attributes from data that do not contribute to ... See full document
5
DM L Based Feature Extraction and Classifier Ensemble for Object Recognition
... DM-L based features are extracted from the pre-trained models using the “activations” function available in Matlab [21] ...external Classifier Ensemble for rec- ognition purposes and this is a new ... See full document
19
Ensemble based Classification Techniques for Concept Drifting in Continuous Data Stream: A Survey
... network based Mobile Real-time Health care Monitoring (WMRHM) framework which has the capacity of giving health predictions online based on continuously monitored real time vital body signals ... See full document
7
Meta Feature Classification to Explore Automatic Detection of Malware Using Segmentation Method
... the ensemble Meta classifier in selecting security domain ...Meta classifier is to identify malware identification in android related micro-soft applications based on real-time ...This ... See full document
5
Hedge Classification with Syntactic Dependency Features Based on an Ensemble Classifier
... an ensemble classifier. The set of features for each classifier are shown in the column named “system” of Ta- ble ...separately, based on their individ- ual set of ...the ensemble ... See full document
6
A meta stacked ensemble probabilistic classifier
... conglomerate approach for criminal’s instigation by the Meta stacked Ensemble Probabilistic Algorithm ...The framework proposes application of phase wise base ensemble classifiers (Xgboost, ... See full document
7
An Ensemble Classifier for the Prediction of Heart Disease
... an ensemble classifier approach has been used for the prediction of heart disease which shows better predictive accuracy than that of individual ...disease based on risk ... See full document
7
CLASSIFYING ARABIC TEXT USING DEEP LEARNING
... the classifier will be ...lexicon-based classifier, they used a word list collected by Hu and Liu (17) and added some words to ...build ensemble classifier by using the Majority Vote ... See full document
12
Simple And Ensemble Decision Tree Classifier Based Detection Of Breast Cancer
... Song[1] et al studied various decision tree algorithms including CART, C4.5, CHAID, and QUEST using SAS and SPSS and analyzed the effectiveness of decision trees.Al- Sahily[2] et al in their study used different decision ... See full document
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SPECTRUM INVESTIGATION FOR SHARING ANALYSIS BETWEEN BWA SYSTEM AND FSS RECEIVER
... [4]. Ensemble technology was introduced to the area of data classification and has since obtained great ...the ensemble method, two criteria are taken into consideration, which are that the ensemble ... See full document
11
A Novel Hybrid Approach Based on Instance Based Learning Classifier and Rotation Forest Ensemble for Spatial Prediction of Rainfall-Induced Shallow Landslides Using GIS
... this method has successfully applied in many fields with high accuracy, including landslide susceptibility [29,32]. To construct the J48 Decision Trees model in this study, 10 pixels per leaf and the confident factor of ... See full document
26
The online performance estimation framework: heterogeneous ensemble learning for data streams
... heterogeneous ensemble technique based on Online Performance Estimation that selects the single best classifier on recent predictions to classify new ...of ensemble members, and the fading ... See full document
28
Design of Ensemble Classifier Selection Framework Based on Ant Colony Optimization for Sentiment Analysis and Opinion Mining
... ants. Ensemble classifier selection is a combinatorial problem and ACO provides a way to solve this problem ...maximum diversity and accuracy reduced to a problem of finding the shortest path from ... See full document
6
Human gait identification from extremely low quality videos : an enhanced classifier ensemble method
... This approach fails whenev- er both the probe and gallery samples are from low frame-rate ...morphing approach for temporal ...period based on multiple periods of low frame-rate gait sequences. ... See full document
28
Emotion Extraction Using Ensemble Classification Model In Data Mining
... an ensemble classifier schema by combining statistical machine learning classification methods and knowledge based approach for the task of recognizing emotions in various domains such as ... See full document
9
Handling Imbalance Class Problem Using Ensemble Classifier
... Hybrid approach that uses data level approach along with the algorithmic approach proposed by ...with ensemble algorithm Balanced Boost to deal with the rare class ...This approach ... See full document
7
SENTIMENT ANALYSIS OF TWEETS USING SUPPORT VECTOR MACHINE
... Anurag P. Jain and Mr. Vijay D. Katkar [10] presented a method to predict sentiments tendency of people towards political situation and issues using data mining classifiers (k- nearest neighbor, RandomForest, BayesNet ... See full document
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