Abstract
The internet is faster than the speed of light, memory storage and computing power has moved to the cloud. Big Data Analytics plays a vital role to segregate the data in some order. There is a huge amount of data available in the Information Industry. This data is of no use until it has converted into useful information. It is necessary to analyse this huge amount of data and extract useful information from it. An algorithm in data mining (or machine learning) is a set of heuristics and calculations that creates a model from data. To create a model, the algorithm first analyses the data you provide, looking for specific types of patterns or trends. The algorithm uses the results of this analysis over much iteration to find the optimal parameters for creating the mining model. These parameters have been applied across the entire data set to extract actionable patterns and detailed statistics. Included in this category is a very advanced technique and tool called “predictive algorithms”. Predictive algorithms have revolutionized the way we view the future of data and have demonstrated the big strides of computing technology. In this paper, we discussed about the criteria used to choose the right predictive model algorithm.
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Gopala Krishnan, C., Golden Julie, E., Harold Robinson, Y. (2020). Predictive Algorithm and Criteria to Perform Big Data Analytics. In: Balas, V., Solanki, V., Kumar, R. (eds) Internet of Things and Big Data Applications. Intelligent Systems Reference Library, vol 180. Springer, Cham. https://doi.org/10.1007/978-3-030-39119-5_16
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DOI: https://doi.org/10.1007/978-3-030-39119-5_16
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