Analysis of Improved ID3 Algorithm using Havrda & Charvat Entropy

Abstract

Data mining is often called as knowledge discovery procedure. We use data mining techniques in order to identify the patterns and relationships among them. Data mining consist of combinations of Machine learning, Visualization for identifying the patterns. Data mining consist of different techniques which can be used to complete a goal. From all the data we need to find the data which will give more information which will help to predict the performance. Data mining techniques allows us to discover hidden patterns, relationship form huge amount of data. Information extracted from large database is helpful in decision making. By referring the extracted information the processing methodologies are selected. The objective of data mining is to identify valid, novel, potentially useful, and understandable correlations and patterns in existing data. Finding useful patterns in data is known by different names (e.g., knowledge extraction, information discovery, information harvesting, data archeology, and data pattern processing)