Classification Rules
Mango Fruit Quality Prediction using Associative Classification Rules
... of rules increased when the minimum confidence thresh- olds were ...of rules is correlated to the predicting ac- curacy, ...of rules results in the higher ac- ...of rules in a rule- based ...
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Knowledge Fusion Technique Using Classifier Ensemble by Different Classification Rules
... ABSTRACT: Classification rules are extracted from sample data known as knowledge. If we extract these knowledge in a distributed way, it is necessary to combine or fuse these rules. The task of data ...
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Small-Sample Error Estimation for Bagged Classification Rules
... the classification of both gene expression data [7–10] and protein-abundance mass spec- trometry data ...overfitting classification rules (the so-called “weak ...
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Classification Rules Mining Model with Genetic Algorithm in Cloud Computing
... Genetic Classification Rules Mining Model (CGCRMM) to address classification rules mining ...of classification is arranged considering the distributed and parallel cloud ...
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International Paralympic Committee Powerlifting Classification Rules and Regulations
... These Classification Rules (referred to generally as “the Rules”) provide a framework within which the process of “Classification” may take ...of Classification is to minimise the ...
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Evolving text classification rules with genetic programming
... compact classification rules using combinations of N-Grams (character ...producing rules that are effective classifiers in terms of precision and recall when evaluated against a set of training ...a ...
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A Genetic Algorithm for Discovering Classification Rules in Data Mining
... data. Classification rule mining aims to discover a small set of rules in the database that forms an accurate ...for classification rule mining have been intensively studied due to the large variety ...
5
Pruning classification rules with instance reduction methods
... Generating classification rules from data often leads to large sets of rules that need to be ...generated rules, without adversely affecting the predictive ...
6
Data mining of range-based classification rules for data characterization
... One popular method that can be employed for mining range based classification rules is the C4.5 algorithm [92]. This is a partitioning based technique that only looks for the best halving of the domain with ...
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Generating Classification Rules from Training Samples
... optimizing classification rules from training samples using fuzzy membership ...extracted classification rules from training samples for these two ...extracted rules, we developed a FIS ...
7
Knowledge Acquisition tool for Classification Rules using Genetic Algorithm Approach
... [1]. Classification Rule Mining (CRM) is a data mining technique for discovering important classification rules from large dataset that is coupled with a set of pre- defined classes ...the ...
6
Training and assessing classification rules with unbalanced data
... the classification rule that best fits the data according to the optimization of some objective ...favour classification rules that perform well only on the frequent class (see the next section for ...
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Rough Set Approach for Generation of Classification Rules for Malaria
... decision-making rules, reduce all redundant objects and attributes and seek the minimum subset of attributes so as to attain satisfying ...generating classification rules from a set of observed ...
5
Classification Rules for Medical Devices a
... actual classification of each device depends on the precise claims made by the manufacturer and on its intended ...actual classification of a particular device must be considered individually, taking ...
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COMBINED METHODOLOGY of the CLASSIFICATION RULES for MEDICAL DATA - SETS
... Data mining is the process of selecting, exploring and modeling large amounts of data in order to discover unknown patterns or relationships which provide a clear and useful result to the data analyst. Medical data ...
5
Classification rules comparison into data mining concept
... indicates as ROC graphical presentation, and that is another way to examine the performance of a specific or multiple classifiers. X-axis indicates false positive rate and Y-axis indicates true positive rate. (0,1) ...
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Optimization of Decision Rules in Fuzzy Classification
... of classification rules is one of the most important tasks of data ...effective rules helps us to make right ...effective rules with high predictive ...
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A Study on Associated Rules and Fuzzy Partitions for Classification
... the classification ac- curacy, a large amount of data is ...generate classification rules, the rules generated will be more statistically ...
8
Evolving rules for document classification
... compact classification rules based on combinations of N-Grams (character ...producing rules that are effective classifiers in terms of precision and recall when evaluated against a set of training ...
13
MapReduce network enabled algorithms for classification based on association rules
... Furnkranz and Widmer [100] proposed a learning algorithm called Incremental Reduced Error Pruning (IREP), which integrates a separate-and-conquer approach with Reduced Error Pruning (REP) [98] .REP was introduced as ...
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