Implementation:DistrictDataLabs Yellowbrick GridSearchColorPlot

Knowledge Sources	DistrictDataLabs_Yellowbrick
Domains	Model_Selection, Visualization
Last Updated	2026-02-08 05:00 GMT

Overview

Concrete tool for visualizing GridSearchCV results as a color-coded heatmap of scores across two hyperparameter dimensions.

Description

The GridSearchColorPlot renders the results of a scikit-learn GridSearchCV as a pcolormesh heatmap where the x and y axes represent two hyperparameters and the color represents the cross-validation score. It automatically projects results onto the specified parameter pair using the param_projection utility.

Usage

Import this visualizer when comparing the effect of two hyperparameters on model performance after a grid search.

Code Reference

Source Location

• Repository: DistrictDataLabs_Yellowbrick
• File: yellowbrick/gridsearch/pcolor.py
• Lines: 1-177

Signature

class GridSearchColorPlot(GridSearchVisualizer):
    def __init__(
        self, estimator, x_param, y_param,
        metric="mean_test_score", colormap="RdBu_r", ax=None, **kwargs,
    ):
        """Grid search heatmap visualizer."""

def gridsearch_color_plot(
    estimator, x_param, y_param, X=None, y=None, ax=None, **kwargs,
):
    """Quick method for grid search color plot."""

Import

from yellowbrick.gridsearch import GridSearchColorPlot
from yellowbrick.gridsearch.pcolor import gridsearch_color_plot

I/O Contract

Inputs

Name	Type	Required	Description
estimator	GridSearchCV	Yes	Fitted or unfitted grid search
x_param	str	Yes	First hyperparameter name
y_param	str	Yes	Second hyperparameter name
metric	str	No	Score metric (default: "mean_test_score")
colormap	str	No	Matplotlib colormap (default: "RdBu_r")

Outputs

Name	Type	Description
ax	matplotlib.Axes	Axes with color-coded heatmap

Usage Examples

from sklearn.model_selection import GridSearchCV
from sklearn.svm import SVC
from yellowbrick.gridsearch import GridSearchColorPlot

grid = GridSearchCV(SVC(), {"C": [0.1, 1, 10], "gamma": [0.01, 0.1, 1]})

viz = GridSearchColorPlot(grid, "param_C", "param_gamma")
viz.fit(X, y)
viz.show()

Related Pages

• Environment:DistrictDataLabs_Yellowbrick_Python_Scikit_Learn_Environment