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[PDF] Top 20 A new genetic algorithm based clustering for binary and imbalanced class data sets

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A new genetic algorithm based clustering for binary and imbalanced class data sets

A new genetic algorithm based clustering for binary and imbalanced class data sets

... the algorithm from drop into the local minimum. Thus, as new generations develop, the quality of the chromosomes or the possible solutions are also ... See full document

36

A kernel based two class classifier for imbalanced data sets

A kernel based two class classifier for imbalanced data sets

... are based on a least squares or a regularized lease squares estimator, with equal weighting for all data points in ...for imbalanced data, will produce unfavorable classifi- cation results for ... See full document

14

Proposing a Novel Cost Sensitive Imbalanced Classification Method based on Hybrid of New Fuzzy Cost Assigning Approaches, Fuzzy Clustering and Evolutionary Algorithms

Proposing a Novel Cost Sensitive Imbalanced Classification Method based on Hybrid of New Fuzzy Cost Assigning Approaches, Fuzzy Clustering and Evolutionary Algorithms

... in data mining is the class imbalance ...the binary case, when there exists a considerable difference between the number of instances in each ...minority class refers to a class with ... See full document

9

Mixture Model Clustering Using Variable Data Segmentation and Model Selection: A Case Study of Genetic Algorithm

Mixture Model Clustering Using Variable Data Segmentation and Model Selection: A Case Study of Genetic Algorithm

... model clustering based on variable data segmentation and model selection will be explained on a data set, known as namely Ruspini data set ...a new approach for determining the ... See full document

10

A new genetic algorithm based polytechnic college course timetabling

A new genetic algorithm based polytechnic college course timetabling

... life data of a Polytechnic ...giving binary weight to teachers there is a limitation in generation of binary weight based on the system ...then binary weight method is faster than ... See full document

7

Binary Real Coded Genetic Algorithm  Based  k Means Clustering for Unit  Commitment Problem

Binary Real Coded Genetic Algorithm Based k Means Clustering for Unit Commitment Problem

... for clustering: The Iterative Self-Organizing Data Analysis Technique (ISODATA) [47], Clustering Large Applications based up on Randomized Search (CLARANS) [48], Parallel-cluster (p-cluster) ... See full document

18

Intelligent Anomaly Detection Techniques for Denial of Service Attacks

Intelligent Anomaly Detection Techniques for Denial of Service Attacks

... a new dataset for the research community by collecting real network traffic data from ...normal data from ...attack data with the help of Labris Networks, an R&D company which specializes ... See full document

12

A Comparative Study on K-Means And Genetic Algorithm For Data Clustering

A Comparative Study on K-Means And Genetic Algorithm For Data Clustering

... grouping Genetic algorithm in clustering, started with proposed encoding, and different modification of crossover and mutation operation and also initiated the local search include with the island ... See full document

9

Clustering for binary data sets by using genetic algorithm incremental K means

Clustering for binary data sets by using genetic algorithm incremental K means

... of clustering algorithms that specifically focus in binary ...of data became the main subject in this research, namely Genetic Algorithms ...(IKM) algorithm to cluster the binary ... See full document

6

Implementation of Clustering based Unit Commitment Employing Particle Swarm Optimization

Implementation of Clustering based Unit Commitment Employing Particle Swarm Optimization

... technique based on principles inspired from the school of fish or swarm of birds ...population based stochastic optimization technique inspired by social behaviour of bird flocking or fish ...obtained. ... See full document

10

A New Partition-based Clustering Algorithm For Mixed Data

A New Partition-based Clustering Algorithm For Mixed Data

... attribute class that represents the central part of the multi Modes way, and expand the traditional Euclidean distance to the mixed data, to reflect the dissimilarity between the objects and ...proposed ... See full document

5

Transfer Learning For Message Passing Algorithm

Transfer Learning For Message Passing Algorithm

... behaviors based on empirical data, such as from sensor data or ...databases[1]. Data mining and machine learning technologies have already achieved significant success in many knowledge ... See full document

10

Diabetes Prediction Using Multiple Machine Learning Algorithm   From The Peoples Data Of Rural Kodagu

Diabetes Prediction Using Multiple Machine Learning Algorithm From The Peoples Data Of Rural Kodagu

... diabetes data analysis and diabetes prediction model Khan et al. Used data mining techniques through Rapid ...ID3 algorithm are used for prediction with 72% and 80% of ...rough sets on the ... See full document

9

HIERARCHICAL CLUSTERING BASED MULTI-DIMENSIONAL POLYGON REDUCTION ALGORITHM FOR LARGE SPATIAL DATA

HIERARCHICAL CLUSTERING BASED MULTI-DIMENSIONAL POLYGON REDUCTION ALGORITHM FOR LARGE SPATIAL DATA

... In COD-CLARANS [13], the authors have represented obstacles through visibility graph and thus computed the obstructed distance between data objects. Also, it detects mostly spherical shaped clusters and depends on ... See full document

12

Genetic Algorithm Based Network Lifetime Enhancement In The Clustered Routing Protocol Of Wireless Sensor NetworkStuti Bhandari, Priyadarshni

Genetic Algorithm Based Network Lifetime Enhancement In The Clustered Routing Protocol Of Wireless Sensor NetworkStuti Bhandari, Priyadarshni

... Unequal clustering has mitigated the pitfalls of equal and balanced clustering by scaling the size of ...them Genetic Algorithm has been a promising approach which ensures the optimized ... See full document

5

Use of Evolutionary Techniques for Symbolic Execution Based Testing

Use of Evolutionary Techniques for Symbolic Execution Based Testing

... this class is domain reduction procedure proposed and used by Demillo et al for its fault based test data generator named as GODZILA ...of binary search algorithm and expression ... See full document

6

A Review on Clustering Analysis based on
Optimization Algorithm for Datamining

A Review on Clustering Analysis based on Optimization Algorithm for Datamining

... – Clustering analysis is one of the important concept of data ...the clustering problem it is one of the research based ...The clustering is belongs to the unsupervised learning in ... See full document

6

Multi Swarm Based Ensemble Clustering

Multi Swarm Based Ensemble Clustering

... the Clustering Approach using the proposed Genetic Algorithm called “Multi Swarm Based Ensemble Clustering ...proposed algorithm improves PSO and PSC in terms of memory and ... See full document

14

Fuzzy partition technique for clustering big urban dataset

Fuzzy partition technique for clustering big urban dataset

... [12]. Clustering can be very useful for between cluster separation, within cluster homogeneity and for good representation of data by its ...Big Data as they require less time and space to ... See full document

6

An Energy Efficient Mechanism using Mutated Bat Algorithm in Wireless Sensor Network

An Energy Efficient Mechanism using Mutated Bat Algorithm in Wireless Sensor Network

... In recent decades, there are researchers and scientists applying analogy from the biological and natural systems. They include operative, distributed as well as intelligent techniques to problem-solving that are observed ... See full document

7

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