In addition to the term knowledge discovery, people also use a number of other terms with similar meanings such as data/pattern analysis, data mining, etc. But in short, in essence, knowledge discovery Knowledge involves analyzing data and using special techniques to find feature patterns in a huge data set. There are many definitions of knowledge discovery that have been given by different authors, according to Fayyad’s definition: “KDD is the non-trivial process of identifying valid, novel, and potentially valid latent patterns. useful and understandable in the data”. The knowledge mining process includes stages: data preparation, pattern search, data mining, pattern evaluation, and use of the discovered knowledge. Each technique has its own advantages and disadvantages and is applied in different data mining purposes. Decision trees are used in classification and prediction problems. K-means algorithm, EM algorithm is used in data clustering problems.