This lecture gives various definitions of Data Mining. It also gives why Data Mining is required. Various examples on Classification , Cluster and Association rules are given.
1. Introduction to Data Mining Dr. Sushil Kulkarni Jai Hind College (sushiltry@yahoo.co.in)
2. — Introduction to database — A Problem and A Solution — What Is Data Mining? — Goal of Data Mining — What is (not) Data Mining? — Convergence of 3 key Technologies — Data mining Functions — Kinds of Data Mining Problems Road Map
38. Definition of Classification Problem Given a database D={t 1 ,t 2 ,…,t n } and a set of classes C={C 1 ,…,C m }, the Classification Problem is to define a mapping f: D C where each t i is assigned to one class .
48. What is a natural grouping among these objects? School Employees Tatkare’s Family Males Females Clustering is subjective
49. What is Similarity? The quality or state of being similar; likeness; resemblance; as, a similarity of features. Similarity is hard to define, but… “ We know it when we see it ” The real meaning of similarity is a philosophical question. We will take a more pragmatic approach. Webster's Dictionary
58. A Weka bird is a strong brown bird which is native to New Zealand and grows to be about the same size as a chicken. The Weka was once fairly common on the North and South Islands of New Zealand but over the years has heavily declined on the North Island due to the major damage of their habitats.