Interactive ipywidget and plotly framework for exploring hyperparameter tuning results
plotly == 4.12.0
ipywidgets == 7.5.1
Clone repo and cd into the project directory
$ git clone https://github.com/oaoni/HyperInteractive.git
$ cd HyperInteractive
Launch in a classic jupyter notebook
$ jupyter notebook
import pandas as pd
from interactivehyper import hyperExplore
data = pd.read_csv('./demo/modeltune.csv')
initial_axis = ['best_test_loss','best_test_corr']
initial_surface_axis = ['mu','alpha','best_test_corr']
legend_group = 'model'
hover_items = ['learning_rate','alpha','mu']
tab = hyperExplore(data,initial_axis,initial_surface_axis,legend_group,hover_items)
tab