Jupyter widgets for hypernets
Project description
hboard-widget
This project provides a visualization tool for experiment information based on jupyter notebook/ jupyterlab widget.
Installation
Install with pip
pip install hboard-widget
Install with conda
conda install -c conda-forge hboard-widget
Install with source code
Build from source code need following requirements:
The project need frontend of hboard to be built in advance.
Clone the source code:
git clone https://github.com/DataCanvasIO/HyperBoard.git
Build for development:
cd ./hboard-widget
pip install -e .
jupyter nbextension install --py --symlink --overwrite --sys-prefix hboard_widget
jupyter nbextension enable --py --sys-prefix hboard_widget
jupyter labextension develop --overwrite hboard_widget
You need to rebuild the JS when you make a code change:
cd ./hboard-widget/js
yarn run build
Example
The following steps shows how to implement the experiment visualization in notebook
- Import the required modules:
import warnings
warnings.filterwarnings('ignore')
from sklearn.model_selection import train_test_split
from hypernets.examples.plain_model import PlainModel, PlainSearchSpace
from hypernets.experiment import make_experiment
from hypernets.tabular.datasets import dsutils
- Create an experiment
df = dsutils.load_boston()
df_train, df_eval = train_test_split(df, test_size=0.2)
search_space = PlainSearchSpace(enable_lr=False, enable_nn=False, enable_dt=False, enable_dtr=True)
experiment = make_experiment(PlainModel, df_train,
target='target',
search_space=search_space,
callbacks=[],
search_callbacks=[])
- Experiment visualization configurations
from hboard_widget import ExperimentSummary
experiment_summary_widget = ExperimentSummary(experiment)
display(experiment_summary_widget)
- Visualize the dataset information
from hboard_widget import DatasetSummary
dataset_summary_widget = DatasetSummary(experiment.get_data_character())
display(dataset_summary_widget)
- Visualize the experiment process
from hboard_widget import ExperimentProcessWidget
estimator = experiment.run(max_trials=3)
widget = ExperimentProcessWidget(experiment)
display(widget)
Find the project in Notebook experiment visualization notebook.ipynb.
Related project
Currently, HyperGBM has integrated this tool. The HyperGBM experiment could call the notebook widget visualization function and display the experiment dashboard. Please refer to HyperGBM: Experiment Visualization in Notebook
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