Data Mining

Extraction of valuable information from vast amounts of unprocessed data is known as data mining. Data mining results have a wide range of applications, and more businesses are investing in this technology. In addition to covering numerous sophisticated techniques, Data Mining: Concepts and Techniques describe all of the basic tools and techniques used in the process.

This book covers new and developing tools and techniques in addition to introducing the basics of data mining. Basic topics in data mining, such as cluster analysis, association rules, OLAP, concept definition, data preparation, classification and prediction, are explained.

Next, more sophisticated data mining methods are covered, such as information extraction from a variety of intricate sources outside relational databases. Time-series databases, spatial databases, object databases, and multimedia databases are examples of this. It also examines gathering information from a variety of online sources and turning it into a usable form.

The chapters in Data Mining: Concepts and Techniques are structured to function as separate sections. This allows teachers to present the lessons in any sequence they desire and select the chapters they want to use as teaching materials.

The objective is to give the reader the background knowledge needed to apply data mining to actual situations by presenting the core ideas and methods for each topic. Characteristics Novel: Owing to advancements in the field, the book delves more deeply into big data and includes updated chapters to reflect these developments.