Naive Bayes game: Difference between revisions
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Naive Bayes is named after Thomas Bayes, a reverend who lived in England in the 18th century. He studied the question that still keeps a lot of people busy these days: what are the chances to win a raffle? The actual formula was invented by Pierre-Simon Laplace, a French mathematician, born in 1749 in Normandy. | Naive Bayes is named after Thomas Bayes, a reverend who lived in England in the 18th century. He studied the question that still keeps a lot of people busy these days: what are the chances to win a raffle? The actual formula was invented by Pierre-Simon Laplace, a French mathematician, born in 1749 in Normandy. | ||
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Revision as of 13:52, 28 February 2019
In machine learning Naive Bayes methods are simple probabilistic classifiers that are widely applied for spam filtering and sentiment analysis.
They require a small amount of training data to estimate the necessary parameters. They can be extremely fast compared to more sophisticated methods. They are difficult to generalise, this means, that they perform on very specific tasks, demanding to be trained with the same style of data that will be used to work with afterwards.
Naive Bayes is named after Thomas Bayes, a reverend who lived in England in the 18th century. He studied the question that still keeps a lot of people busy these days: what are the chances to win a raffle? The actual formula was invented by Pierre-Simon Laplace, a French mathematician, born in 1749 in Normandy.