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ENH Rework narrative of GBDT notebook #763

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merged 8 commits into from
May 17, 2024
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ArturoAmorQ
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Originally I wanted to rework only the wording, as well explaining the GBDT algo is the cornerstone for understanding HGBT. But then I decided to factorize the code by introducing a helper function to keep the focus on the narrative other than the code.

@glemaitre glemaitre self-requested a review April 26, 2024 14:14
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Here are some comments.

python_scripts/ensemble_gradient_boosting.py Outdated Show resolved Hide resolved
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# %%
import pandas as pd
import numpy as np

# Create a random number generator that will be used to set the randomness
rng = np.random.RandomState(0)
rng = np.random.RandomState(0) # Create a random number generator
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Let's move the generator next to the data generation. We should avoid showing a pattern where people would use the generator across different function and estimators.
So the best practice is just to show it next to the data generation. we could even slightly change the code and have:

def generate_data(n_samples=50, seed=0):
    rng = np.random.default_rng(seed)
    x = rng.normal(size=(n_samples,)) * ...
    noise = rng.normal(size=(s_samples,)) * 0.3

using default_rng should be encourage nowadays.

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@glemaitre glemaitre merged commit 31bfaaf into INRIA:main May 17, 2024
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github-actions bot pushed a commit that referenced this pull request May 17, 2024
Co-authored-by: ArturoAmorQ <[email protected]>
Co-authored-by: Guillaume Lemaitre <[email protected]> 31bfaaf
@ArturoAmorQ ArturoAmorQ deleted the gbdt_wording branch May 17, 2024 09:19
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2 participants