Stock Market Pattern Recognition Algorithm

Data mining is the process of extracting patterns from data. Stock Market Pattern recognition is a very active research area which overlaps with various other research fields such as Machine Learning, Data Mining, Probability Theory, Algebra and Calculus. In recent years the concept of data mining has emerged as one of them. The main focus of the experiment is on the mining algorithms to analyze a much accurate and efficient algorithm. Data mining is becoming an increasingly important tool to transform these data into information. It is commonly used in a wide range of profiling practices, such as marketing, surveillance, fraud detection and scientific discovery. Time series is used for prediction for value. Different classifier method has been analyzed. First, in this project we are interested in the comparison of the quality of different mining algorithms.Data mining can be defined as an activity that extracts some new nontrivial information contained in large databases.