Full API

.visualize()

Display a 4-panel matplotlib figure. Requires matplotlib - install with pip install matplotlib or pip install "fling[viz]".

Classifier panels

Panel	What it shows
Confusion Matrix	Heatmap of true vs predicted labels
Per-class Metrics	Precision / Recall / F1 bar chart per class
ROC Curve	AUC score + shaded curve (binary)
Feature Importances	Horizontal bar chart of top 12 features

Panel	What it shows
Actual vs Predicted	Scatter plot with perfect-prediction diagonal and R² annotation
Residuals vs Predicted	Scatter with zero line and ±1 RMSE shaded band
Residual Distribution	Histogram with mean marker and zero-error line
Feature Importances	Horizontal bar chart; falls back to stat tiles if model doesn't support importances

python

model = Classifier(data="titanic.csv", target="Survived")
model.train()
model.visualize()   # opens the 4-panel figure