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# Random-Forest-Algorithm I used the random forest algorithm to find the bank note authentication in this project. In this case, I used Photos of genuine and forged banknote-like specimens were used to obtain information. An industrial camera, usually used for print inspection, was used for digitization. The final images have a resolution of 400…

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Random-Forest-Algorithm

Random-Forest-Algorithm I used the random forest algorithm to find the bank note authentication in this project. In this case, I used Photos of genuine and forged banknote-like specimens were used to obtain information. An industrial camera, usually used for print inspection, was used for digitization. The final images have a resolution of 400x400 pixels. Gray-scale picturing is possible due to the object lens and distance to the examined object. It was possible to obtain images with a resolution of about 660 dpi. To extract features from images, the Wavelet Transform method was used.
Dataset link : https://www.kaggle.com/ritesaluja/bank-note-authentication-uci-data
The project's frontend was built with Flask, and it was deployed on Heroku. The requirements.txt file includes all of the dependencies. Run App.py after all dependencies have been installed.

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# Random-Forest-Algorithm I used the random forest algorithm to find the bank note authentication in this project. In this case, I used Photos of genuine and forged banknote-like specimens were used to obtain information. An industrial camera, usually used for print inspection, was used for digitization. The final images have a resolution of 400…

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