TY  - JOUR
T1  - Review of Data Preprocessing Techniques in Data Mining
AU - Alasadi, Suad A. AU - S. Bhaya, Wesam 
JO  - Journal of Engineering and Applied Sciences
VL  - 12
IS  - 16
SP  - 4102
EP  - 4107
PY  - 2017
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2017.4102.4107
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2017.4102.4107
KW  - Data mining
KW  -data preprocessing
KW  -data set
KW  -KDD (Knowledge Discovery in Databases)
KW  -dataset
KW  -pattein
AB  - 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.
ER  -