Heatmap

Heatmap visualization for correlation matrices in trainedml.

This module provides the HeatmapViz class, which generates correlation heatmaps using matplotlib and seaborn, supporting various correlation methods and masking options.

Mathematical context

Pearson, Spearman, Kendall correlation
Masking upper triangle for symmetric matrices

Exemples

>>> from trainedml.viz.heatmap import HeatmapViz
>>> viz = HeatmapViz(df)
>>> viz.vizs()
>>> viz.figure.show()

class trainedml.viz.heatmap.HeatmapViz(data, features='all', method='pearson', mask=True, save_path: str | None = None)[source]

Bases : Vizs

Correlation heatmap visualization.

Paramètres:

data (pandas.DataFrame) – The dataset.
features ('all' or list, default='all') – Features to include.
method (str, default='pearson') – Correlation method (“pearson”, “spearman”, “kendall”).
mask (bool, default=True) – Whether to mask the upper triangle.

data

The data.

Type:: pandas.DataFrame

features

Features used.

Type:: list

method

Correlation method.

Type:: str

mask

Masking option.

Type:: bool

figure

The generated figure (after calling vizs).

Type:: matplotlib.figure.Figure

Exemples

>>> viz = HeatmapViz(df, features=['A', 'B'])
>>> viz.vizs()
>>> viz.figure.show()

vizs()[source]: Calcule la matrice de corrélation et affiche la heatmap.