Q. What is Data mining?

Data mining: Data mining is the process of extracting patterns from data. Data mining is seen as an increasingly important tool by modern business to transform data into an informational advantage. It is now used in a wide range of profiling practices, like surveillance, marketing and scientific discovery.

Data mining generally involves 4 classes of tasks: 

• Clustering - is the task of discovering groups and structures in the data which are in some way or another 'similar', without using known structures in the data.

• Classification - is the task of generalising known structure to apply to new data. For instance, an email program may attempt to classify an email as legitimate or spam. Common algorithms comprise decision tree learning, naive Bayesian classification, nearest neighbour, neural networks and support vector machines.

• Regression - tries to find a function that models the data with least error.

• Association rule learning - Searches for relationships between variables. For illustration a supermarket may gather data on customer purchasing habits. Using association rule learning, supermarket can determine that products are frequently bought together and use this information for marketing purposes. This is sometimes designated as market basket analysis.