shaiknawazshareef/eeg-steady-state-visual-signal-analysis-using-machine-learning

How shaiknawazshareef/eeg-steady-state-visual-signal-analysis-using-machine-learning works

This is a compact EEG/SSVEP analysis script: an analyst uploads a CSV, the script loads and imputes it, explores the data, prepares a feature/target split, trains regression and classification models, and evaluates results. It also runs an SVM pipeline and cross-validated grid search. The README describes these capabilities, and the excerpted script shows their implementation; all internal components therefore point to the same source file. The README mentions a notebook, but the supplied tree contains only the Python script and CSV.

Main entry points: eeg_steady_state_visual.py Feature and target split · A001SB1_1.csv EEG CSV

Components 14

Data preparation

Colab upload eeg_steady_state_visual.py
EEG CSV A001SB1_1.csv
Load and impute eeg_steady_state_visual.py
Data exploration eeg_steady_state_visual.py
Feature and target split eeg_steady_state_visual.py

Modeling

Linear regression eeg_steady_state_visual.py
RANSAC regression eeg_steady_state_visual.py
Perceptron eeg_steady_state_visual.py
Logistic regression eeg_steady_state_visual.py
Decision tree eeg_steady_state_visual.py
SVM pipeline eeg_steady_state_visual.py
SVM grid search eeg_steady_state_visual.py

Evaluation

Model evaluation eeg_steady_state_visual.py

Other components

Analyst

Connections 19

Analyst → Colab upload: uploads data eeg_steady_state_visual.py
Colab upload → EEG CSV: selects file eeg_steady_state_visual.py
EEG CSV → Load and impute: read and impute eeg_steady_state_visual.py
Load and impute → Data exploration: visualizes eeg_steady_state_visual.py
Load and impute → Feature and target split: selects and splits eeg_steady_state_visual.py
Feature and target split → Linear regression: fits eeg_steady_state_visual.py
Feature and target split → RANSAC regression: fits eeg_steady_state_visual.py
Feature and target split → Perceptron: fits eeg_steady_state_visual.py
Feature and target split → Logistic regression: fits eeg_steady_state_visual.py
Feature and target split → Decision tree: fits eeg_steady_state_visual.py
Feature and target split → SVM pipeline: fits eeg_steady_state_visual.py
Feature and target split → SVM grid search: fits on full data eeg_steady_state_visual.py
Linear regression → Model evaluation: scores predictions eeg_steady_state_visual.py
RANSAC regression → Model evaluation: scores predictions eeg_steady_state_visual.py
Perceptron → Model evaluation: scores predictions eeg_steady_state_visual.py
Logistic regression → Model evaluation: scores predictions eeg_steady_state_visual.py
Decision tree → Model evaluation: scores predictions eeg_steady_state_visual.py
SVM pipeline → Model evaluation: scores predictions eeg_steady_state_visual.py
SVM grid search → Model evaluation: selects by accuracy eeg_steady_state_visual.py

Drawn by GitDiagram on November 10, 2026 from the repository's file tree, README and source files. Read as Markdown ·