Data Mining is the methods to mine useful information from avalanche of data.
I think method called "data mining" has characteristics below.
Data mining is not only one of multivariable analysis but particular method
because "multivariable" is not appropriate to some method.
Upper characteristics 3 is not common in multivariable analysis.
In the literature, neural networks and Bayesian networks are sometimes introduced as data mining companions. The method that came out after the so-called " multivariate analysis " is collectively called "data mining", so it seems that it is classified in this way.
However, I don't think the point of "mining" the important part from the pile of data is true. This site classifies it as artificial intelligence (AI) .
The outputs of Decision Tree and Cluster Analysis are similar. Both of them use the tree-type graph.
The difference between decision Tree and Cluster Analysis is very similar to the difference between Multi-Regression Analysis and Principal Component Analysis . The former use the information of "Y" data in its analysis. But the latter does not use "Y" data. The former analyze the relationship between Y and Xs. The latter analyze the relationship among Xs.
Selection of Methods
Statistical Way of Making Hypothesis
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