Cognitive Emotion

About the Project

The project uses the EEG Brainwave Dataset from Kaggle to create machine learning models that allow the user to predict the emotion of a person given his EEG Brainwave Data.The dataset was downloaded from Kaggle. Here is the link to the dataset.

Setup

To run the notebook one can either prefer using Google Colab the better method or run the notebook locally. To run using Colab just use the link at the end of the ReadMe file.

For running the notebook locally, follow the steps [Windows]:

1. Clone the repository using git clone https://github.com/Namratha2301/CognitiveEmotion.git
2. Set directory to cloned repo cd CognitiveEmotion
3. Create a python virtual environment for the project using python -m venv env
4. Activate the environment using env\Scripts\activate
5. Install the dependencies using pip install -r requirements.txt
6. Open the Jupyter Notebook IDE using jupyter notebook
7. The Jupyter Notebook IDE should open up allowing you to run the file

Machine Learning Models and Scores

S.No	Model	Package	Score
1	Random Forest Classifier	SciKit-Learn	98.7%
2	Logistic Regression Classifier	SciKit-Learn	93.2%
3	Logistic Regression Classifier With 2 PC	SciKit-Learn	77.5%
4	Logistic Regression Classifier with 10 PC	SciKit-Learn	86.6%
5	Linear Support Vector Machine Classifier (SVM)	SciKit-Learn	96.57%
6	Extreme Gradient Boosting Classifier	XGBoost	99.39%
7	GRU	TensorFlow	95.46%

Link to Colab File

CognitiveEmotionColab