Data Mining Algorithms for Disaster Data Analysis
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Nowadays, data analysis becomes more important and essential to get accurate knowledge and making good decisions. Data mining research helps to carry out indepth data analysis for different kinds of data, from which, we can infer the hidden knowledge. "Data Mining Algorithms for Disaster Data Analysis" performed a detailed analysis on disaster data set using classification algorithms. The classification algorithms used in this analysis are IBK, KStar, LWL, J48, Random Forest, Random Tree, Naïve Bayes, Tree Decision Stump, Single Rule Induction, CHAID, QUEST, Exhaustive CHAID and CRT. This com...
Nowadays, data analysis becomes more important and essential to get accurate knowledge and making good decisions. Data mining research helps to carry out indepth data analysis for different kinds of data, from which, we can infer the hidden knowledge. "Data Mining Algorithms for Disaster Data Analysis" performed a detailed analysis on disaster data set using classification algorithms. The classification algorithms used in this analysis are IBK, KStar, LWL, J48, Random Forest, Random Tree, Naïve Bayes, Tree Decision Stump, Single Rule Induction, CHAID, QUEST, Exhaustive CHAID and CRT. This comparative analysis is implemented in three different data mining tools, WEKA, Rapidminer and SPSS. This book studied the data mining basics and also described how to perform classification tasks using these tools. This information will be useful for the students, researchers and professionals to pursue their work in the area of data mining.
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