Білім беру бағдарламасының атауы мен шифры 6В0720 Мұнай-газ ісі, 6В07203Металлургия, 6В07106 Электроэнергетика

1. 
   Data analysis
   
2. 
   Data Mining Bases
   

To create the plan of data collection it is necessary to:

1. 
   Define problems and formulate research objectives.
   
2. 
   Realize a preliminary study of an interesting subject.
   
3. 
   Develop concepts of research.
   
4. 
   Make detail planning of a research.
   
5. 
   Make a selection of information sources and collection of secondary data.
   
6. 
   Estimate the obtained data and to make a decision how primary data are needed.
   
7. 
   Define a method of collection of primary data – inquiry, observation, experiment.
   
8. 
   Carry out directly the collection of primary information.
   
9. 
   Provide results of the research (presentation).
   

All problems, which are solved by a tree method, can be integrated in the following three classes:

1) Data description: Decision trees allow storing information about data in the compact form, instead of them we can store a decision tree, which contains the exact description of objects.

2) Classification: Decision trees perfectly cope with tasks of classification, i.e. reference of objects to one of in advance known classes. The target variable shall have discrete values.

3) Regression: If a goal variable has continuous values, decision trees allow setting the dependence of the goal variable on independent (input) variables. For example, the tasks of numerical prediction (prediction of values of a goal variable) belong to this class.

Data Mining can consist of two or three stages.

Stage 1. Detection of regularities (free search).

Stage 2. Use of revealed regularities for prediction of unknown values (prognostic simulation).

Stage 3. Analysis of exceptions is the stage intended for detection and explanation of anomalies which are found in regularities.

Бекіту сұрақтары

1. 
   What is data analysis?
   
2. 
   What is data?
   
3. 
   How can forecasting data methods be classified?
   
4. 
   What is the regression in data analysis?
   
5. 
   What is data visualization?
   
6. 
   What is Data Mining?
   
7. 
   What are data mining methods?
   
8. 
   What is a decision tree?
   
9. 
   What are the tasks of Data mining?
   
10. 
    What are the algorithms of creation of a decision tree?