ABSTRACT:

Data mining is a modern area of science of extracting useful information from large data sets or databases. Applications of Data mining can be found in various areas. This paper introduces new contributions by optimization as a key technology in data mining. The methods suggested for solution of such important problems as where it deals with large data.

EXISTING SYSTEM :

Data Mining is the process of automatic discovery of useful information in large data repositories. Generally, Data Mining can be divided into two categories according to the objective of algorithms: 1) Classification Analysis 2) Association Analysis. Many Data Mining methods involve with mathematical programming techniques. Optimization can be a component of a larger Data Mining process and New Data Mining techniques can be built using entirely optimization-based method. These optimization-based Data Mining techniques are applied mainly in Classification Analysis, where as very few algorithms in Association Analysis based as optimization.

PROPOSED SYSTEM: Logical Analysis of data is another Optimization Based Approach algorithm. It builds a classifier for a binary target variable based on learning a logical expression that can distinguish between positive and negative examples in a data set. If same data set is nonbinary, cut-off value is applied to convert them into binary variable. And a table with all the binary attributes and target variables are obtained. The objective then becomes to explore a partially defined Boolean function (pdbf), with all the binary attributes as input and target variables as output.

SYSTEM REQUIREMENTS
SOFTWARE REQUIREMENTS:
• Programming Language : Python
• Font End Technologies : TKInter/Web(HTML,CSS,JS)
• IDE : Jupyter/Spyder/VS Code
• Operating System : Windows 08/10

HARDWARE REQUIREMENTS:

 Processor : Core I3
 RAM Capacity : 2 GB
 Hard Disk : 250 GB
 Monitor : 15″ Color
 Mouse : 2 or 3 Button Mouse
 Key Board : Windows 08/10