rule-based classifier decision
Framework of Classification Algorithms
... ABSTRACT: Data mining is a standout amongst the most critical research areas in the field of computer science. Data mining systems are utilized for separating the hidden learning from the extensive databases. There are ...
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Classification Techniques for Intrusion Detection – An Overview
... for classifier algorithm selection for each attack ...used classifier algorithms that represent a wide variety of fields: Bayesian approach, decision trees, rule based models and lazy ...
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A Massively Parallel Deep Rule Based Ensemble Classifier for Remote Sensing Scenes
... The segmentation layer uses a sliding window to partition the remote sensing images into smaller pieces for local information extraction. By changing the size of the sliding window, the level of granularity of the ...
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Decision Degree-based Decision Tree Technology for Rule Extraction
... of decision tree induc- tion is disadvantageous in terms of scope, depth, and accuracy when compared with ID3, and the other approaches are still based on the algorithm of ID3, the structure of these ...
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A Fuzzy Classifier based on Product and Sum Aggregation Reasoning Rule
... A decision tree is a predictive model that, as its name implies, can be viewed as a ...of decision tree is used in many areas because it has many advantages ...of decision tree is its instability and ...
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Image Edge Detection by Using Rule Based Fuzzy Classifier
... Over the past few decades fuzzy logic has been used a wide range of problem domains .Although the fuzzy logic is relatively young theory, the area of applications are wide: process control, management and decision ...
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Comparative Study of the Performance of M5 Rules Algorithm with Different Algorithms
... conjunctive rule learner, M5-Rules Algorithm and decision table majority classifier is compared for Modeling of Effort Estimation of Software ...is based on the cost fa- ctors in COCOMO ...
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Performance Evaluation of Lazy, Decision Tree Classifier and Multilayer Perceptron on Traffic Accident Analysis
... association rule mining to know the, unlike circumstances that happen at a very high rate in road accident areas on Belgium ...clustered based data might fetch information at a higher level as compared ...
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Hybrid Decision Tree and Naïve Bayes Classifier for Predicting Study Period and Predicate of Student’s Graduation
... The decision tree method transforms a fact into a decision tree that represents the ...rule. Decision tree algorithm has a high degree of accuracy but has long computational time while naïve ...
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An Experimental Analysis of Various Data Mining Techniques for Software Bug Classification
... Tree, Rule Based Classifier, Naïve Bayesian and SVM Classifiers are the eager learners, because in these approaches using the training data, classification model is constructed before the receiving ...
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“Interval Type-2 Fuzzy Logic Rule based Data mining for Steam Turbine Fault Analysis of a Power System Rotatory Machine Component”
... Fuzzy decision tree or Soft Decision Tree (SDT) classifier using interval type-2 fuzzy logic rule based data mining for steam turbine fault analysis of a power system rotatory machine ...
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Survey on Types of Bug Reports and General Classification Techniques in Data Mining
... different rule based classification techniques namely Decision tree, PART, RIPPER and RIDOR based on tuple-id propagation ...four rule based classifier across multiple ...
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Building an Effective Intrusion Detection System using combined Signature and Anomaly Detection Techniques
... signature based detection and anomaly based detection was ...C4.5 decision tree (J48) as classifier was used to generate signature based model and then frequent itemsets with ...
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Decision tree–based classifier in providing telehealth service
... the decision tree-building algorithm, we build the decision tree for each expert and discuss the per- formance and the rules of each decision ...these decision trees for the testing data ...
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A cascade of deep learning fuzzy rule based image classifier and SVM
... DLFRB classifier is able to perform highly accurate classification on the handwriting digits in the majority cases by following the “winner takes all” ...DLFRB classifier follows is not an effective ...
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Knowledge-based Systems and Interestingness Measures: Analysis with Clinical Datasets
... medical decision support sys- tem ( MDSS ) , clinical decision support system [ 4 ] , clinical recommender system [ 5 ] , predic- tion system, and various other machine learn- ing models [ 6-9 ] , are used ...
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Multitude Classifier Using Rough Set Jelinek Mercer Naïve Bayes for Disease Diagnosis
... Disease Classifier algorithm for efficient identification of classes that helps in measuring the relationship between disease ...Disease Classifier al- ...obtained. Based on the disease features, ...
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Performance Analysis of Channel Equalizers in Optical Communication for Next Generation Systems
... a classifier by domain experts) are a very good effectiveness, considerable savings in terms of expert labor power, and straightforward portability to different ...
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Computational modelling to track human emotion trajectories through time : a thesis presented to Massey University in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Computer Science at School of Engineering and Advanced Technology, Massey University, Palmerston North, New Zealand
... Emotions vary continuously with regard to intensity, duration, persistence with time, and other attributes. In addition, their appearance on the face varies, and the transition in facial expressions is based on ...
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Vol 2, No 12 (2014)
... flexible rule- based system that let users to adapt the filtering criterion to be applied to their walls and a Machine Learning-based soft classifier automatically labelling messages in ...
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