shubhamkumar2202 / analysis-on-advertisment-data

This project is on whether the internet user clicked on ad or not. Its a model that will predict the whether the user will click on the ad or not based off the feature of that user

Analysis-on-advertisment-data

This model predicts whether the user will click on an advertisment or not based off the feature of that user.Using unsupervised learning algorithms (machine learning) and some visualization tools

Dataset overview

Solution

Logistic Regression

Decision Tree

Conclusion

The obtained results showed the use value of both machine learning models. The Decision Tree model showed slightly better performance than the Logistic Regression model, but definitely, both models have shown that they can be very successful in solving classification problems.

The prediction results can certainly be changed by a different approach to data analysis. We encourage you to do your analysis from the beginning, to find new dependencies between variables and graphically display them. After that, create a new training set and a new test set. Let the training set contain a larger amount of data than in the article. Fit and evaluate your model. In the end, praise yourself in a comment if you get improved performances.