ConceptPythonBeginner Overfitting: why the model that fits its data best predicts worst model = make_pipeline(MinMaxScaler((-1, 1)), PolynomialFeatures(d), LinearRegression())
ToolPythonIntermediate RDKit from the ground up: water solubility from a molecule's structure lin = LinearRegression().fit(X[train], y[train])lin_s = LinearRegression().fit(X[train_s], y[train_s])l = root_mean_squared_error(y[te], LinearRegression().fit(X[tr], y[tr]).predict(X[te]))