#
Visualization methods

Methods for visualizing evaluations results:

##
Radar Plot

####
evaluate.visualization.radar_plot

< source >

( data model_names invert_range = [] config = None fig = None )

Parameters

- data (`List[dict]`) — the results (list of metric + value pairs). E.g. data = [{“accuracy”: 0.9, “precision”:0.8},{“accuracy”: 0.7, “precision”:0.6}]
- names (`List[dict]`) — model names. E.g. names = [“model1”, “model 2”, …]
- invert_range (`List[dict]`, optional) — the metrics to invert (in cases when smaller is better, e.g. speed) E.g. invert_range=[“latency_in_seconds”]
- config (`dict`, optional) — a specification of the formatting configurations, namely:

  - rad_ln_args (`dict`, default `{"visible": True}`): The visibility of the radial (circle) lines.

  - outer_ring (`dict`, default `{"visible": True}`): The visibility of the outer ring.

  - angle_ln_args (`dict`, default `{"visible": True}`): The visibility of the angle lines.

  - rgrid_tick_lbls_args (`dict`, default `{"fontsize": 12}`): The font size of the tick labels on the scales.

  - theta_tick_lbls (`dict`, default `{"fontsize": 12}`): The font size of the variable labels on the plot.

  - theta_tick_lbls_pad (`int`, default `3`): The padding of the variable labels on the plot.

  - theta_tick_lbls_brk_lng_wrds (`bool`, default `True` ): Whether long words in the label are broken up or not.

  - theta_tick_lbls_txt_wrap (`int`, default `15`): Text wrap for tick labels

  - incl_endpoint (`bool`, default `False`): Include value endpoints on calse

  - marker (`str`, default `"o"`): the shape of the marker used in the radar plot.

  - markersize (`int`, default `3`): the shape of the marker used in the radar plot.

  - legend_loc (`str`, default `"upper right"`): the location of the legend in the radar plot. Must be one of: ‘upper left’, ‘upper right’, ‘lower left’, ‘lower right’.

  - bbox_to_anchor (`tuple`, default `(2, 1)`: anchor for the legend.

- fig (`matplotlib.figure.Figure`, optional) — figure used to plot the radar plot.

Create a complex radar chart with different scales for each variable Source: https://towardsdatascience.com/how-to-create-and-visualize-complex-radar-charts-f7764d0f3652

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