Authors : Suad A. Alasadi and Wesam S. Bhaya
Abstract: Data mining is the process of extraction useful patterns and models from a huge dataset. These models and patterns have an effective role in a decision making task. Data mining basically depend on the quality of data. Raw data usually susceptible to missing values, noisy data, incomplete data, inconsistent data and outlier data. So, it is important for these data tobe processed before being mined. Preprocessing data is an essential step to enhance data efficiency. Data preprocessing is one of the most data mining steps which deals with data preparation and transformation of the dataset and seeks at the same time to make knowledge discovery more efficient. Preprocessing include several techniques like cleaning, integration, transformation and reduction. This study shows a detailed description of data preprocessing techniques which are used for data mining.
Suad A. Alasadi and Wesam S. Bhaya, 2017. Review of Data Preprocessing Techniques in Data Mining. Journal of Engineering and Applied Sciences, 12: 4102-4107.