Open AccessAn Applied N C Differentiation Interpolation technique for improved random Anomalous values in Data Mining
Author(s) -
Darshanaben Dipakkumar Pandya,
Abhijeetsinh Jadeja,
Sheshang Degadwala
Publication year - 2022
Publication title -
international journal of scientific research in science, engineering and technology
Language(s) - English
Resource type - Journals
eISSN - 2395-1990
pISSN - 2394-4099
DOI - 10.32628/ijsrset229218
Subject(s) - interpolation (computer graphics) , numerical differentiation , computation , interval (graph theory) , set (abstract data type) , numerical analysis , numerical integration , mathematics , computer science , argument (complex analysis) , algorithm , mathematical analysis , combinatorics , programming language , animation , biochemistry , chemistry , computer graphics (images)
In data mining, the word “interpolation” refers to interpolating some anonymous information from a given set of known information. The method of interpolation is extensively used as a valuable tool in science and engineering. The predicament is a classical one and dates back to the time of Newton, who needed to solve such a problem in analyzing data on the numerical computations. Numerical applications of interpolation include derivation of computational techniques for numerical differentiation, numerical integration and numerical solutions of differential equations. In this paper a closest fit Application of the formula to numerical data for recovering haphazard Anomalous values in Data Mining has been shown in the case of representing the data on the dataset global carbon dioxide emissions from fossil fuel burning by Fuel Type corresponding as a method of time. The formula is suitable in the situation where the values of the argument are at equal interval.