List of Machine Learning Algorithms
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High Quality Content by WIKIPEDIA articles! High Quality Content by WIKIPEDIA articles! Averaged One-Dependence Estimators (AODE) is a probabilistic classification learning technique. It was developed to address the attribute-independence problem of the popular Naive Bayes classifier. It frequently develops substantially more accurate classifiers than naive Bayes at the cost of a modest increase in the amount of computationLike naive Bayes, AODE does not perform model selection and does not use tuneable parameters. As a result, it has low variance. It supports incremental learning whereby the ...
High Quality Content by WIKIPEDIA articles! High Quality Content by WIKIPEDIA articles! Averaged One-Dependence Estimators (AODE) is a probabilistic classification learning technique. It was developed to address the attribute-independence problem of the popular Naive Bayes classifier. It frequently develops substantially more accurate classifiers than naive Bayes at the cost of a modest increase in the amount of computationLike naive Bayes, AODE does not perform model selection and does not use tuneable parameters. As a result, it has low variance. It supports incremental learning whereby the classifier can be updated efficiently with information from new examples as they become available. It predicts class probabilities rather than simply predicting a single class, allowing the user to determine the confidence with which each classification can be made. Its probabilistic model can directly handle situations where some data are missing.
