Powered by PCA Dimensionality Reduction + Random Forest Logic. Trained on UCI Heart Disease Data.
The Red Dot represents your current patient. Its position is calculated by projecting the 5 clinical inputs onto the first two Principal Components derived from the training set.
We use a linear projection matrix. Your inputs are scaled and multiplied by eigenvector coefficients to plot the 2D coordinate.
We simulate the ensemble by aggregating weighted thresholds (Entropy/Gini) for the 5 selected features.