Cancer Identification Data Mining Java Project

  • rajith
  • 28 Jun 2018
  • Java

Cancer Identification Data Mining Java Project Code, Document

Abstract:

“Cancer Identification from DNA Microarray Gene Expression Data and its Statistical Analysis” is a web application which provides a comprehensive study that focuses on exploring the main objectives used in the cancer microarray gene expression. This application provides a challenging task as microarray which is having high dimension-low sample dataset with a lot of noisy or irrelevant genes and missing data. This application also provides the approaches that have been applied using cancer microarray gene expression. Dimensionality reduction technique for removing the irrelevant genes is applied in this application. An efficient gene selection technique with higher accuracy and also which takes minimum computational time is developed in this application.

Existing System:

In the existing system, the data is provided incompletely which has a lot of scope for lacking attribute values, lacking certain attributes of interest, or containing only aggregate data. In the existing system there is noisy data containing errors or outliers. In the existing system, there is an inconsistent data that containing discrepancies in codes or names.

Proposed System:

The proposed system provides various preprocessing techniques like data cleaning, data integration, data transformation, data reduction and data discretization. The proposed system efficient and advanced technologies are developed in processing the data. This system fills in missing values, smooth noisy data, identify or remove outliers, and resolve inconsistencies. The proposed system uses multiple databases, data cubes, or files.

Software Requirements:

Hardware Requirements:

Processor-Intel Core, RAM-2 Gb, Hard disk-500 Gb.

Software Requirements:

Operating System-Windows 7/8/10, Front End-HTML, CSS, JavaScript Back End-Oracle, MySql, Language-Java, Server Side Programming Tool-JSP, Web Server-Apache Tomcat.

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