Open source library for the Datrics models deserialization
Project description
Descripton
Open source library for the Datrics models deserialization
Initial source
The solution is based on https://github.com/mlrequest/sklearn-json library
Getting Started
datrics-json makes importing the models imlemented in the Datrics AI platform from their JSON representation
Install
pip install datrics-json
Example Usage
import datrics_json as datjson
model_dict = datjson.from_json(file_name)
deserialized_model = list(model_dict.get('trained_models').values())[0]['model']
sample_data = model_dict.get('sample_data')['input']
deserialized_model.predict(sample_data)
Features
sklearn-json requires scikit-learn >= 0.22.2. LightGBM >= 2.3.1
Supported scikit-learn Models
- sklearn.linear_model.LogisticRegression
- sklearn.ensemble.IsolationForest
- sklearn.clustering.KMeans
- sklearn.clustering.DBSCAN
- sklearn.linear_model.LinearRegression
- sklearn.linear_model.Ridge
- sklearn.linear_model.Lasso
- sklearn.linear_model.ElasticNet
Supported lightGBM Models
- lightgbm.LGBMClassifier - binary - Gradient Boosting Trees
- lightgbm.LGBMClassifier - multiclass - Gradient Boosting Trees
- lightgbm.LGBMClassifier - binary - Random Forest
- lightgbm.LGBMClassifier - multiclass - Random Forest
- lightgbm.LGBMRegressor - Gradient Boosting Trees
- lightgbm.LGBMRegressor - Random Forest
Test data
Project details
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