Difference between revisions of "Datamining: Classification"
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+ | Classification is a data mining task of predicting the value of a categorical variable (target or class) by building a model based on one or more numerical and/or categorical variables (predictors or attributes). | ||
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+ | Four main groups of classification algorithms are: | ||
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+ | Frequency Table | ||
+ | ZeroR | ||
+ | OneR | ||
+ | Naive Bayesian | ||
+ | Decision Tree | ||
+ | Covariance Matrix | ||
+ | Linear Discriminant Analysis | ||
+ | Logistic Regression | ||
+ | Similarity Functions | ||
+ | K Nearest Neighbors | ||
+ | Others | ||
+ | Artificial Neural Network | ||
+ | Support Vector Machine | ||
Latest revision as of 10:47, 1 August 2017
sumber: http://www.saedsayad.com/classification.htm
Classification is a data mining task of predicting the value of a categorical variable (target or class) by building a model based on one or more numerical and/or categorical variables (predictors or attributes).
Four main groups of classification algorithms are:
Frequency Table ZeroR OneR Naive Bayesian Decision Tree Covariance Matrix Linear Discriminant Analysis Logistic Regression Similarity Functions K Nearest Neighbors Others Artificial Neural Network Support Vector Machine