More options to ensemble your models
Project description
MoreModels
A python library allowing you to use multiple models using the weight of each model based on their performance
install using
pip install moremodels
Example code:
from moremodels import WeightedModels
model1 = catboost.CatBoostRegressor()
model2 = RandomForestRegressor()
model3 = xgboost.XGBRegressor()
my_data = pd.read('my_data.csv')
test = pd.read('test.csv)
my_models = [model1, model2, model3]
models = WeightedModels( models = my_models, trainSplit = 0.8, randomState = 696969 )
models.fit(my_data)
print(models.modelWeights)
myPredictedData = models.predict(test)
print(models.models[0])
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
moremodels-1.0.3.tar.gz
(3.1 kB
view hashes)
Built Distribution
Close
Hashes for moremodels-1.0.3-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 3d16927319e146948b2c8991076ee3c9c5867bbeee4e7da653861a315e60d7a0 |
|
MD5 | 3e89f0d8021a7f1a10596f7f9cdd1c92 |
|
BLAKE2b-256 | 36f826c3c4b619e4f32ac51744dbb8eaa662a0b0c77ac32b416ab598da3ffb7d |