@article{MAKHILLJEAS2017121614723,
    title = {Review of Data Preprocessing Techniques in Data Mining},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {12},
    number = {16},
    pages = {4102-4107},
    year = {2017},
    issn = {1816-949x},
    doi = {jeasci.2017.4102.4107},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2017.4102.4107},
    author = {Suad A. and},
    keywords = {Data mining,data preprocessing,data set,KDD (Knowledge Discovery in Databases),dataset,pattein},
    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.}
    }