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-1.0.2.tar.gz
(3.0 kB
view hashes)
Built Distribution
Close
Hashes for moremodels-1.0.2-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 5a0a785b5b304ea6919471d06cd72886bb511354b72342d54c4aea0e9b11331c |
|
MD5 | aadd3d915342684ee1b5f01ebf12976d |
|
BLAKE2b-256 | ec36cf2a6c430b16a965c63f0a6720b876d307f9b41b526528e37473aff6b712 |