Classification is one of the most important tasks for different application such as text categorization, tone recognition, image classification, micro-array gene expression, proteins structure predictions, data Classification etc. Most of the existing supervised classification methods are based on traditional statistics, which can provide ideal results when sample size is tending to infinity. However, only finite samples can be acquired in practice. In this paper, a novel learning method, Support Vector Machine (SVM), is applied on different data (Diabetes data, Heart Data, Satellite Data and Shuttle data) which have two or multi class. SVM, a powerful machine method developed from statistical learning and has made significant achievement in some field. Introduced in the early 90’s, they led to an explosion of interest in machine learning. The foundations of SVM have been developed by Vapnik and are gaining popularity in field of machine learning due to many attractive features and promising empirical performance. SVM method does not suffer the limitations of data dimensionality and limited samples  & .
In our experiment, the support vectors, which are critical for classification, are obtained by learning from the training samples. In this paper we have shown the comparative results using different kernel functions for all data samples.
India has emerged as an ‘IT Super power’, especially in the field of software and related services export. The paper is an attempt to discern and delineate the growth performance, challenges and opportunities of such a promising sector of Indian economy. It has been observed that software export has registered an annual compound growth rate of 45 per cent during the last decade and continues to show robust growth even today. Growing respect for Indian software industry in the international market, continued rise in the offshore services, quality services, timely delivery, entry into new markets, Y2K data conversion business, international linkages and also due to various steps taken by the Government to promote software export such as simplifying procedures, tax concessions, establishments of software technology parks, more liberal foreign investment policies, possessement of second largest pool of scientific and skilled manpower which is also English speaking, low cost of labour, locational time difference with the western world enabling round the clock development, pro-active role by Nasscom (the software industry association), etc. are some of the factors that gave fillip to the faster growth of India’s software export. Undoubtedly other developing countries can learn lessons from India’s experience and can develop IT capabilities by mutual cooperation.