This repository is consists with a Google Colab script which I used to classify my research dataset.
The research was done to find the user preferences on various color palettes on websites.
Dataset was created after a survey and the survey was done with the help of a Google Form.
In this script you can find the codes for,
- Random Over Sampling using "imbalanced-learn" library. Documentation
- Dataset manipulation using "scikit-learn" library. Documentation
- Support Vector Machine (SVM) Classifier package of scikit-learn library.
- Decision Tree Classifier of scikit-learn library.
- Printing Decision Tree in textual format
- Printing Decision Tree in graphical format
- Naive Bayes Classifier
- Gaussian Naive Bayes
- Categorical Naive Bayes
- XGBoost Classifier
- Printing Tree in graphical format
- Random Forest Classifier
Required datasets are uploaded to this repository itself. Feel free to contact me for any references.
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