Author : Penugonda Ravikumar 1
Date of Publication :14th March 2017
Abstract: Classification of time series data is one of the popular fields nowadays. Many algorithms exist to get accurate and faster result which speeds up the computation. Nowadays E-Commerce sites are providing many user convenient options like recommendations for the products that they are purchasing which are playing key role in attracting the users to visit their sites. All these are happening based on the classification of data. Home automation is one of the evolving technologies in which data storage is important. It will be convenient if we are able to compare test data with limited trained data by preserving accuracy. Some data such as national security, personal information, bank details must be very confidential which has to be stored very securely. These all comes under time series data and data such as images, weather reports, speeches, and satellites data can be converted into time series data. Classification of normal data can be done by normal methods like nearest neighbor but to classify Time Series data by taking all these above features into consideration is difficult because time series data has to convert into structured format and it has to be sort and compare according to time Some existing algorithms are quite good in classifying Time Series data by satisfying some of these features. There are many algorithms which can classify data of different types quite accurately. But all algorithms might not satisfy all factors. So based on type of data we have to choose appropriate algorithm.
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