A) What is Data Mining? Describe Data Mining Characteristics/Objectives.

B) Describe the process of building SVM

C) Describe the Text Mining Process

Answer:

A

• Data mining is the process of extracting information from data which helps in decision making.
• it is also called as knowledge discovery from data
• in data mining, we apply certain algorithms to obtain information otherwise called as knowledge pattern from data
• Characteristics are
  • Data mining is market-oriented: its applications are used to find business-oriented information that can be used by the managers to make decisions.
  • Users are Data analyst and knowledge workers
  • Data mining is subject oriented: it is concentrated into a specific subject
  • Data mining uses multidimensional data structures to store data, called data cubes
  • data mining is performed upon historical data which are not frequently updated

B

• SVM (Support vector machine)
• Support vector machine is a classification technique in data mining.
• SVM classify data into different classes based on their features.
• The basic idea behind SVM is to plot a hyperplane that classifies the data into two classes
• we can plot more than one hyperplane but we have to find a hyperplane which is optimum
• the optimum hyperplane is a hyperplane that posses a maximum margin(the distance between support vectors of different classes ) as shown in the image below

C)

Text Mining Process

• Text mining is the process of extracting information from huge and unstructured text files
• text mining has high importance and application since the digital text files are accumulating day to day in every business organization.
• The steps in text mining are as follows the
  • first step is data preprocessing: in this step, text files are accumulated from different external resources and they are cleaned to remove syntactic and semantic errors
  • Next step is feature selection: that is selecting the appropriate features to perform mining operation
  • Then the algorithms are applied to perform the actual mining operation
  • After the mining, the information is displayed using interpretation and visualization

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