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• W2321810412 abstract "Cluster examination is data mining task for the assignment of collection a set of items in such a path, to the point that questions in the same gathering (called a cluster) are more like one another than to those in different gatherings (clusters). K-means grouping is a technique for group investigation which intends to parcel n perceptions into k groups in which every perception fits in with the cluster with the closest mean. This paper, decided the aftereffect of standard parameter estimations of shading picture division with k-means and the modified k-means with ABC and ACO algorithms.The paper demonstrates that division of color picture with modified k-mean consolidated with swarm Intelligence calculations for color image segmentation gives preferable results over simple k-means and Modified k-means with Ant colony optimization gives better results than modified k-means with Artificial bee colony . Keywords— Data mining, clustering, k-means algorithm, swarm intelligence, artificial bee colony, ant colony." @default.
• W2321810412 created "2016-06-24" @default.
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• W2321810412 date "2015-08-30" @default.
• W2321810412 modified "2023-09-26" @default.
• W2321810412 title "Twitter Crossfire: Terror Attack Detection via Probabilistic Classifiers" @default.
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• W2321810412 doi "https://doi.org/10.14257/ijdta.2015.8.4.05" @default.
• W2321810412 hasPublicationYear "2015" @default.
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