Eye Blinks Detection Dashboard
Random Bits Forest Model Performance Analysis
Generated: 2025-11-02 00:44:38
1
Model Trained
94.29%
Accuracy
14
Brain Voxels
14,980
Samples
About This Dataset
Dataset: Eye Blinks Detection using EEG Brain Signals
Features: 14 brain voxels (X1-X14) representing different regions of brain activity
Target: Binary classification - Blink detected (1) or No blink (0)
Model: Random Bits Forest (RBF) - Specialized ensemble method for binary classification
Special Note: This dataset has the target column in the same file as features, making it ideal for testing model compatibility
Model Performance
RBF model achieved 94.29% accuracy in detecting eye blinks from brain activity patterns.
Feature Importance Analysis
Brain voxels ranked by their importance in predicting eye blinks. Voxel X2 shows the strongest correlation with blink events.
Performance Visualizations
ROC Curve
Confusion Matrix
Training Time
Top Features
