Skip to main content

Feature embeddings with LightGBM

Project description

LightGBM Embeddings

Feature embeddings with LightGBM

Installation

pip install lightgbm-embedding

Examples

import pandas as pd
from sklearn.model_selection import train_test_split
from lightgbm_embedding import LightgbmEmbedding

df = pd.read_csv(
    "https://gist.githubusercontent.com/curran/a08a1080b88344b0c8a7/raw/0e7a9b0a5d22642a06d3d5b9bcbad9890c8ee534/iris.csv"
)
cols = df.columns[:-1]
target = df.columns[-1]
num_classes = df[target].nunique()

X_train, X_test = train_test_split(
    df, test_size=0.2, stratify=df[target], random_state=42
)

n_dim = 20
emb = LightgbmEmbedding(n_dim=n_dim)
emb.fit(X_train[cols], X_train[target])
X_train_embed = emb.transform(X_train[cols])
X_test_embed = emb.transform(X_test[cols])

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

lightgbm_embedding-0.1.2.tar.gz (4.5 kB view hashes)

Uploaded Source

Built Distribution

lightgbm_embedding-0.1.2-py3-none-any.whl (5.2 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page