Data mining techniques have been widely used for extracting knowledge from large amounts of data. Monitoring deforestation is utmost important for the developing countries. Classification of ...

Incomplete data affects classification accuracy and hinders effective data mining. The following techniques are effective for working with incomplete data. The ISOM-DH model handles incomplete data ...

The second step in data mining process is the application of various modeling techniques. These are used to calibrate the parameters to optimal values. Techniques employed largely depend on analytic ...

Alexandra Twin has 15+ years of experience as an editor and writer, covering financial news for public and private companies. Natalya Yashina is a CPA, DASM with over 12 years of experience in ...

This article is published by AllBusiness.com, a partner of TIME. What is "Data Mining?" Data mining is the process of extracting useful patterns, correlations and insights from large datasets using ...

Predictive analytics enables you to develop mathematical models to help you better understand the variables driving success. Predictive analytics relies on formulas that compare past successes and ...

The Journal of Developing Areas, Vol. 50, No. 5, Special Issue on the Kuala Lumpur Conference, November 23-24, 2015 (2016), pp. 371-381 (11 pages) The growing interest in the credit industry resulted ...

With the massive expansion of information technology, the demand for data mining also grew hugely. But data mining — or the process of wading through huge amounts of data and finding what you consider ...