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.
Graphs of Disribution are useful to study data visually.
Some people classify Bayesian Network and Neural Network as methods of data mining. I think they call "data mining" for next generation of Multi-Variable Analysis .
But the approaches of these methods are not "mining". In this HP, these methods are classified in other fields.
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
TStatistical Way of Making Hypothesis
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