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Use parallel coordinates plot to analyse multiple experiments¶
Outline¶
- Fetch multiple experiments and analyse the relations between parameters, metrics and properties.
- Save visualization as html (optionally).
- Setup the visualization to your liking.
- Inspect experiments lineage.
Before we start, make sure that you have dependencies installed¶
neptune-client
neptune-contrib[viz]
hiplot
Example notebooks in Neptune¶
These notebooks are tracked in Neptune public projects. You are free to play with the plots - they are interactive.
Learn more¶
Check integration documentation for more details.
Set project¶
Remember to set the project before you call visualization function
[ ]:
import neptune
from neptunecontrib.viz.parallel_coordinates_plot import make_parallel_coordinates_plot
neptune.init('USERNAME/example-project')
Make and save visualization to standalone html file¶
[ ]:
# magic happens here :)
# use parameter 'html_file_path' to save interactive plot to standalone html file.
make_parallel_coordinates_plot(html_file_path='my_visual.html',
metrics= ['epoch_accuracy', 'epoch_loss', 'eval_accuracy', 'eval_loss'],
params = ['activation', 'batch_size', 'dense_units', 'dropout', 'learning_rate', 'optimizer'],
tag='optuna')
Customize visualization to your need¶
- Set axes order,
- Drop unused axes,
- Apply coloring to axis,
- Sort by clicking on axis,
- Select range in axis & slide.
Inspect experiments lineage¶
- Right-click on the axis name,
- Use options ‘Set as X axis’ and ‘Set as Y axis’ (in the menu XY group at the bottom),
- When both are selected, you will see lineage plot below parallel coordinates plot.
Visualize axis distribution¶
- Right-click on the column name,
- Select “View distribution” at the bottom,
- You will see distribution chart below the parallel plot.