skml-json 1.0.1

Export scikit-learn>=1.4.0 model files to JSON for sharing or deploying predictive models with peace of mind. Original by Mathieu Rodrigue

skml-json

Export scikit-learn model files to JSON for sharing or deploying predictive models with peace of mind.

Why skml-json?

Other methods for exporting scikit-learn models require Pickle or Joblib (based on Pickle). Serializing model files with Pickle provides a simple attack vector for malicious users-- they give an attacker the ability to execute arbitrary code wherever the file is deserialized. For an example see: https://www.smartfile.com/blog/python-pickle-security-problems-and-solutions/.

skml-json is a safe and transparent solution for exporting scikit-learn model files.

Safe

Export model files to 100% JSON which cannot execute code on deserialization.

Transparent

Model files are serialized in JSON (i.e., not binary), so you have the ability to see exactly what's inside.

Getting Started

makes exporting model files to JSON simple.

Install

pip install skml-json

Example Usage

import skml_json as skmljson
from sklearn.ensemble import RandomForestClassifier

model = RandomForestClassifier(n_estimators=10, max_depth=5, random_state=0).fit(X, y)

skmljson.to_json(model, file_name)
deserialized_model = skmljson.from_json(file_name)

deserialized_model.predict(X)

Features

skml-json requires scikit-learn >= 1.4.0.

Supported scikit-learn Models

• Classification

  • sklearn.linear_model.LogisticRegression
  • sklearn.linear_model.Perceptron
  • sklearn.discriminant_analysis.LinearDiscriminantAnalysis
  • sklearn.discriminant_analysis.QuadraticDiscriminantAnalysis
  • sklearn.svm.SVC
  • sklearn.naive_bayes.GaussianNB
  • sklearn.naive_bayes.MultinomialNB
  • sklearn.naive_bayes.ComplementNB
  • sklearn.naive_bayes.BernoulliNB
  • sklearn.tree.DecisionTreeClassifier
  • sklearn.ensemble.RandomForestClassifier
  • sklearn.ensemble.GradientBoostingClassifier
  • sklearn.neural_network.MLPClassifier

• Regression

  • sklearn.linear_model.LinearRegression
  • sklearn.linear_model.Ridge
  • sklearn.linear_model.Lasso
  • sklearn.svm.SVR
  • sklearn.tree.DecisionTreeRegressor
  • sklearn.ensemble.RandomForestRegressor
  • sklearn.ensemble.GradientBoostingRegressor
  • sklearn.neural_network.MLPRegressor