Linear regression with sklearn
Using generated data
- examples/ml/basic_linear_regression.ipynb
- examples/ml/use_basic_linear_expression.ipynb
examples/ml/basic_linear_regression_predict.py
from joblib import load import sys if len(sys.argv) < 2: exit(f"Usage: {sys.argv[0]} Xes") input_values = [] for val in sys.argv[1:]: input_values.append([float(val)]) model = load('linear.joblib') print(model.predict(input_values))