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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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