lightgbm_embedding

Name	lightgbm_embedding JSON
Version	0.2.0 JSON
	download
home_page	None
Summary	Feature embeddings with LightGBM
upload_time	2025-01-12 11:24:35
maintainer	None
docs_url	None
author	Atilla Karaahmetoğlu
requires_python	<3.14,>=3.9
license	MIT
keywords	lightgbm embeddings
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            # LightGBM Embeddings

Feature embeddings with LightGBM

## Installation

    pip install lightgbm-embedding

## Examples
```python
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])
```

            

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    "description": "# LightGBM Embeddings\n\nFeature embeddings with LightGBM\n\n## Installation\n\n    pip install lightgbm-embedding\n\n## Examples\n```python\nimport pandas as pd\nfrom sklearn.model_selection import train_test_split\nfrom lightgbm_embedding import LightgbmEmbedding\n\ndf = pd.read_csv(\n    \"https://gist.githubusercontent.com/curran/a08a1080b88344b0c8a7/raw/0e7a9b0a5d22642a06d3d5b9bcbad9890c8ee534/iris.csv\"\n)\ncols = df.columns[:-1]\ntarget = df.columns[-1]\nnum_classes = df[target].nunique()\n\nX_train, X_test = train_test_split(\n    df, test_size=0.2, stratify=df[target], random_state=42\n)\n\nn_dim = 20\nemb = LightgbmEmbedding(n_dim=n_dim)\nemb.fit(X_train[cols], X_train[target])\nX_train_embed = emb.transform(X_train[cols])\nX_test_embed = emb.transform(X_test[cols])\n```\n",
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