Data mining tasks

Data mining tasks

• 1.
  KHWAJA AAMER
• 2.
  The process ofcollecting, searching through, and analyzing a large amount of data in a database, as to discover patterns or relationships  extraction of useful patterns from data sources, e.g., databases, data warehouses, web.  Patterns must be valid, novel, potentially useful, understandable.
• 3.
   Data isgrowing at a phenomenal rate n Users expect more sophisticated information  Traditional techniques are infeasible for raw data  Human analysts may take weeks to discover useful information  Much of the data is never analyzed at all
• 5.
  Predictive:- It makesprediction about values of data using known results from different data or based on historical data. Descriptive:- It identifies patterns or relationship in data, it serves as a way to explore properties of data.
• 6.
  discovery of afunction that classifies a data item into one of several predefined classes.  Given a collection of records Each record contains a set of attributes, one of the attributes is the class. Ex:-pattern recognition
• 7.
   The valueof attribute is examined as it varies over time  A time series plot is used to visualize time series  Ex:- stock exchange
• 8.
   Clustering isthe task of segmenting a diverse group into a number of similar subgroups or clusters.  Most similar data are grouped in clusters  Ex:-Bank customer
• 9.
   Abstraction orgeneralization of data resulting in a smaller set which gives general overview of a data.  alternatively , summary type information can be derived from data.