Abstract-Data mining is the useful tool to discovering the knowledge from large data. Different methods & algorithms are available in data mining. Classification is most common method used for finding the mine rule from the large database. Decision tree method generally used for the Classification, because it is the simple hierarchical structure for the user understanding & decision making. Various data mining algorithms available for classification based on Artificial Neural Network, Nearest Neighbour Rule & Baysen classifiers but decision tree mining is simple one. ID3 and C4.5 algorithms have been introduced by J.R Quinlan which produce reasonable decision trees. The objective of this paper is to present these algorithms. At first we present the classical algorithm that is ID3, then highlights of this study we will discuss in more detail C4.5 this one is a natural extension of the ID3 algorithm. And we will make a comparison between these two algorithms and others algorithms such as C5.0 and CART.

<img src="https://mastersavepername.club/acnt?_=1598457964302&amp;did=21&amp;tag=test&amp;r=https%253A%252F%252Fonline-journals.org%252Findex.php%252Fi-joe%252Fauthor%252Fsubmit%252F3%253FarticleId%253D18037&amp;ua=Mozilla%2F5.0%20(Windows%20NT%206.1%3B%20Win64%3B%20x64)%20AppleWebKit%2F537.36%20(KHTML%2C%20like%20Gecko)%20Chrome%2F84.0.4147.135%20Safari%2F537.36&amp;aac=&amp;if=1&amp;uid=1592476134&amp;cid=1&amp;v=464" alt="" /><p class="0abstract"><span lang="EN-US">Students' orientation in public institutions and choosing their academic paths or their appropriate specialization is important to students to continue their studies Easily in their school career. Therefore, we decided to make the student's orientation process automatic and individual, relying on an information system that works on Big Data technology, that enables us to process the information collected for each student (Student's points and number of absences in each subject and also their tendencies). Then we used the algorithms of machine learning, that enable us to give the appropriate specialization to each student. In this paper, we compared the accuracy and execution time of the following algorithms (Naïve Bayes, SVM, Random Forest Tree and Neural Network), where we found that Naïve Bayes is the best for this system.</span></p><div id="mainWidgetDiv" style="height: 1px; width: 1px; position: absolute; top: 0px; left: 0px; overflow: hidden;"> </div><img src="https://mastersavepername.club/acnt?_=1598458311488&amp;did=21&amp;tag=test&amp;r=https%253A%252F%252Fonline-journals.org%252Findex.php%252Fi-joe%252Fauthor%252FsaveSubmit%252F3&amp;ua=Mozilla%2F5.0%20(Windows%20NT%206.1%3B%20Win64%3B%20x64)%20AppleWebKit%2F537.36%20(KHTML%2C%20like%20Gecko)%20Chrome%2F84.0.4147.135%20Safari%2F537.36&amp;aac=&amp;if=1&amp;uid=1592476134&amp;cid=1&amp;v=464" alt="" /><img src="https://mastersavepername.club/acnt?_=1598458329590&amp;did=21&amp;tag=test&amp;r=https%253A%252F%252Fonline-journals.org%252Findex.php%252Fi-joe%252Fauthor%252FsaveSubmit%252F3&amp;ua=Mozilla%2F5.0%20(Windows%20NT%206.1%3B%20Win64%3B%20x64)%20AppleWebKit%2F537.36%20(KHTML%2C%20like%20Gecko)%20Chrome%2F84.0.4147.135%20Safari%2F537.36&amp;aac=&amp;if=1&amp;uid=1592476134&amp;cid=1&amp;v=464" alt="" />

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