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2. UNIVERSITY SCHOOL OF MANAGEMENT AND ENTREPRENEURSHIP
3. MBA

Title:	MODEL BUILDING FOR PREDICTION OF AD-CLICKS: AN ML APPROACH
Authors:	Anand, Vishakha
Keywords:	AD CLICKS MACHINE LEARNING SPSS
Issue Date:	31-May-2020
Description:	Machine Learning has now variety of applications in real world whether it is for predictive analysis or automating things or decision making for business purpose. We have done a project which is a Machine Learning approach. This project is about predicting the ad click rate of a customer, based on certain features. We found this problem interesting and therefore made a Machine Learning model to predict the Ad click. This model we have made can be made on different platforms such as SPSS, R, Excel, python etc. We have chosen SPSS and Excel. In this project, we worked on an advertising dataset, indicating whether or not a particular internet user has clicked on an Advertisement. The goal is to predict if a user would click on an advertisement based on the features of the user. We are using a training dataset to find the logic that will be applied on the Test dataset to find the result. We are using two models namely Logistic Regression and Random forest model to predict whether the user will click on the Ad or not. At then we will produce a confusion matrix to analyze how accurate was the prediction that was made on the basis of these two models.
URI:	http://dspace.dtu.ac.in:8080/jspui/handle/repository/18741
Appears in Collections:	MBA

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