Visualize

niaarm.visualize.grouped_matrix_plot(rules, metrics, k=5, interactive=False)

Visualize rules as grouped matrix plot. :param rules: Association rules to visualize :type rules: Rule :param metrics: Metrics to display in visualization_examples. :type metrics: tuple :param k: Number of clusters or groups to display :type k: int :param interactive: Make plot interactive. Default: False :type interactive: bool

Returns:

Figure or plot.

niaarm.visualize.hill_slopes(rule, transactions)

Visualize rule as hill slopes.

Reference: Fister, I. et al. (2020). Visualization of Numerical Association Rules by Hill Slopes. In: Analide, C., Novais, P., Camacho, D., Yin, H. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2020. IDEAL 2020. Lecture Notes in Computer Science(), vol 12489. Springer, Cham. https://doi.org/10.1007/978-3-030-62362-3_10

Parameters:

  • rule (Rule) – Association rule to visualize.

  • transactions (pandas.DataFrame) – Transactions as a DataFrame.

Returns:

Figure and Axes of plot.

Return type:

tuple[matplotlib.figure.Figure, matplotlib.axes.Axes]

niaarm.visualize.scatter_plot(rules, metrics, interactive=False)

Visualize rules/rule as scatter plot :param rules: Association rule or rules to visualize. :type rules: Rule :param metrics: Metrics to display in visualization_examples. Maximum of 2 metrics. :type metrics: tuple :param interactive: Make plot interactive. Default: False :type interactive: bool

Returns:

Figure or plot.

niaarm.visualize.two_key_plot(rules, metrics, interactive=False)

Visualize rules as a two key plot with two primary metrics (support, confidence) and rule order.

Parameters:

  • rules (Rule) – Association rule or rules to visualize.

  • metrics (tuple) – Two metrics to display on the x and y axes. ‘order’ will be used for point color.

  • interactive (bool) – Make plot interactive. Default: False.

Returns:

Figure or plot.