Predicting Consumer Behavior in Online Shopping Environments: An EEG-Based Machine Learning Approach - Raw EEG Data, Matlab Scripts, and Results"

This dataset contains raw Electroencephalogram (EEG) recordings, Matlab programming scripts, and machine learning results associated with the research paper titled "Predicting Consumer Behavior in Online Shopping Environments: An EEG-Based Machine Learning Approach." The EEG data were collected from 33 participants in a controlled laboratory setting, using a low-end EEG device. The Matlab scripts include data preprocessing, feature extraction, and machine learning algorithms, specifically focusing on the K-Nearest Neighbors (KNN) classifier.

The machine learning results demonstrate the predictive accuracy of various classifiers, with KNN outperforming Random Forest (RF), Linear Discriminant Analysis (LDA), and Support Vector Machines (SVM).The dataset aims to provide a comprehensive resource for researchers interested in neuromarketing, consumer behavior, and machine learning applications in predicting consumer choices. It is particularly relevant for those who wish to understand the neural mechanisms underlying decision-making processes in online shopping contexts.