Data Mining, Classification, And Association Rules

1654 Words7 Pages
Abstract: Classification is one of the most familiar data mining technique and model finding process that is used for transmission the data into different classes according to particular condition. Further the classification is used to forecast group relationship for precise data instance. It is generally construct models that are used to predict potential statistics trends. The major objective of machine data is to perfectly predict the class for each record. This article focuses on a survey on different classification techniques that are mostly used in data-mining.
Keywords: Data mining, Classification, decision tree, neural network.
Data mining is one of the many applications of machine learning. Or knowledge discovery in database as it is also known as the non-incidental origin of implicit, in the past strange and potentially information derived from various different sources and convert it into future analyses. Data mining encompasses a number of technical approaches to solve various tasks. Such techniques are clustering, classification, neural networks, regression, and association rules. Data mining is the task of discovering interesting patterns from large amount of data where the data can be stored in databases. In data mining knowledge can be fetched and right to use transforming the tasks from exiting knowledge. Data mining consists of other than gathering and organization of data. [1].Classification is the task of discovers the known structure to

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