HyperGBM: Experiment Visualization in Notebook

This section demonstrates how to visualize a HyperGBM experiment in Jupyter Notebook. With the visualization tool, you could:

1. check the experiment configurations

2. check the dataset information

3. check the processing information

To use these features, an additional package needs to be installed:

pip install hboard-widget

Example

1. import the required packages

import warnings
warnings.filterwarnings('ignore')

from hypernets.utils import logging

from sklearn.model_selection import train_test_split

from hypergbm import make_experiment
from hypernets.tabular.datasets import dsutils

1. creat an experiment

df = dsutils.load_bank()

df_train, df_test = train_test_split(df, test_size=0.8, random_state=42)

experiment = make_experiment(df_train, target='y')
experiment

The experiment configurations is shown as below:

1. plot the dataset information

experiment.plot_dataset()

The output information is shown below:

1. plot the processing information

experiment.run(max_trials=20)

The output information is shown below:

Check the Notebook example hypegbm_experiment_notebook_visualization.ipynb