vastorbit.machine_learning.vast.svm.LinearSVR.contour¶
- LinearSVR.contour(nbins: int = 100, chart: PlottingBase | TableSample | Axes | mFigure | Figure | None = None, **style_kwargs) PlottingBase | TableSample | Axes | mFigure | Figure¶
Draws the model’s contour plot.
- Parameters:
nbins (int, optional) – Number of bins used to discretize the two predictors.
chart (PlottingObject, optional) – The chart object to plot on.
**style_kwargs – Any optional parameter to pass to the Plotting functions.
- Returns:
Plotting Object.
- Return type:
obj
Examples
Let’s consider we’ve fitted a model
model.Contour plot is another useful plot that can be produced for models with two predictors.
model.contour()
Important
Machine learning models with two predictors can usually benefit from their own contour plot. This visual representation aids in exploring predictions and gaining a deeper understanding of how these models perform in different scenarios. Please refer to Contour Plot for more examples.