Exporting Models

Predictive models can be saved and re-used. Models are saved in Python pickle format.


Save model

Models first require data for training. They output a trained model, which can be saved with Save Model widget in the pickle format.

Load model

Models can be reused in different Orange workflows. Load Model loads a trained model, which can be used in Predictions and elsewhere.

Load in Python

Models can also be imported directly into Python and used in a script.

import pickle

with open('model.pkcls', 'rb') as model:
    lr = pickle.loads(model)

>> LogisticRegressionClassifier(skl_model=LogisticRegression(C=1,
                                class_weight=None, dual=False, 
                                fit_intercept=True, intercept_scaling=1.0, 
                                l1_ratio=None, max_iter=10000, 
                                multi_class='auto', n_jobs=1, penalty='l2', 
                                random_state=0, solver='lbfgs', tol=0.0001, 
                                verbose=0, warm_start=False))