Preface:
Because it is a professional statistics, and a recent project involves the inside knowledge of data mining, so taking the time to sum up the knowledge of data mining, if inappropriate, hope you readers correction.
More purposeful when mainly want to talk about the concept of data mining as well as some details about the data, relatively speaking, the theoretical content above normal, but a better understanding of these things will make you do data mining.
1. Data Mining
Definitions: In the large data store, the automatic discovery process to useful information.
The general process of data mining include the following several aspects:
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Data preprocessing
After determining the data set, the data preprocessing starts so that the data can be used for us. Including data cleaning, data integration, data protocols and data conversion method.
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Data Mining
The structural characteristics generally carried out into a specific model and to calculate, using some criteria to judge the performance of different models, or combinations of models, to determine a final model is most appropriate for our post-treatment
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After-treatment
Post-treatment process is equivalent to that we have discovered that we want to find patterns, we will go, or use it in a suitable manner to indicate its use.
General procedure 2. Data Mining
3. Some common data mining algorithms
Reference Links: https://blog.csdn.net/sinat_22594309/article/details/74923643