python-scikit-learnHow to load ML model from file
import pickle
from sklearn import datasets, linear_model
X, y = datasets.load_diabetes(return_X_y=True)
model = pickle.load(open('/tmp/model.ml', 'rb'))
y_pred = model.predict(X)ctrl + cfrom sklearn importimport module from scikit-learn | datasets.load_diabetesloads sample diabetes database |
pickle.load(loads data from given file | open(opens file descriptor (for reading in our case) |
/tmp/model.mlpath to file to load model from | .predict(predict target variable based on given features dataset |
Usage example
import pickle
from sklearn import datasets, linear_model
X, y = datasets.load_diabetes(return_X_y=True)
model = pickle.load(open('/tmp/model.ml', 'rb'))
y_pred = model.predict(X)
print(model.score(X, y))output
0.506799948108825
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