Review on Predictive Analysis of Placement of Students Using Machine Learning Algorithms

DOI

10.2991/978-94-6463-136-4_4How to use a DOI?

Keywords

Machine learning; Decision tree; Logistic Regression; SVM; Random Forest

Abstract

Machine learning is an emerging trend which has proven to learn automatically from past data. Machine learning can be performed using various ways like supervised, unsupervised, reinforcement learning. Machine learning where system computer system learning from the data set available. Machine learning using supervised learning can be performed using either regression or classifier algorithms. In this research paper we have worked on machine learning algorithms which are SVM, Decision Tree, Logistic regression and Random Forest. Using Machine learning algorithms we can build mathematical model and make the predictions using dataset. To make prediction we can go for supervised learning where output will be in the form either yes or No, 0 or 1, in this case either student placed or not placed.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Vinod S. Agrawal
AU  - Sarika Shelke Kadam
PY  - 2023
DA  - 2023/05/01
TI  - Review on Predictive Analysis of Placement of Students Using Machine Learning Algorithms
BT  - Proceedings of the International Conference on Applications of Machine Intelligence and Data Analytics (ICAMIDA 2022)
PB  - Atlantis Press
SP  - 23
EP  - 30
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-136-4_4
DO  - 10.2991/978-94-6463-136-4_4
ID  - Agrawal2023
ER  -