The correct answer is: D. None of the mentioned
Data fishing is a term used to describe the act of searching through large amounts of data in the hope of finding something interesting or useful. It is often used in the context of data mining, where large amounts of data are analyzed in order to find patterns or trends.
Data bagging is a technique used in machine learning to reduce variance in the results of a learning algorithm. It does this by creating multiple training sets from the original data set and then training the algorithm on each of the training sets. The results of the algorithm are then averaged to produce a more accurate result.
Data booting is a technique used in machine learning to reduce bias in the results of a learning algorithm. It does this by creating multiple training sets from the original data set and then training the algorithm on each of the training sets. The results of the algorithm are then averaged to produce a more unbiased result.
Data merging is the process of combining two or more data sets into a single data set. This can be done for a variety of reasons, such as to increase the size of the data set, to combine data from different sources, or to create a more complete data set.
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