Understanding the automl.show_models() output

[RaviGprec]

I'm confused with below outputs where trainin score is around 71% and testing score is around69%. But Dont see 71% or 69% is the show_models() output.

what is the first value in automl.show_models() out put. What is this 0.26000 value ? it is accuracy of the model?
[(0.260000, SimpleRegressionPipeline({'categorical_encoding:choice': 'one_hot_encoding', 'imputation:strategy': 'median', 'preprocessor:choice': 'polynomial', 'regressor:choice': 'liblinear_svr', 'rescaling:choice': 'none', 'categorical_encoding:one_hot_encoding:use_minimum_fraction': 'False', 'preprocessor:polynomial:degree': 2, 'preprocessor:polynomial:include_bias': 'True', 'preprocessor:polynomial:interaction_only': 'False', 'regressor:liblinear_svr:C': 103.11030493878376, 'regressor:liblinear_svr:dual': 'False', 'regressor:liblinear_svr:epsilon': 0.3011904329496452, 'regressor:liblinear_svr:fit_intercept': 'True', 'regressor:liblinear_svr:intercept_scaling': 1, 'regressor:liblinear_svr:loss': 'squared_epsilon_insensitive', 'regressor:liblinear_svr:tol': 1.0974773655165751e-05},
dataset_properties={
'task': 4,
'sparse': False,
'multilabel': False,
'multiclass': False,
'target_type': 'regression',
'signed': False})),

[Robotuks]

From what I understand, 0.26 is a weight for this method. So if you have multiple methods in your model, the output of model is Output = weight1*method1_output + weight2*method2_output + ...

Is this a full output of your .show_models()? Because for me there are usually multiple methods and sum of their weights is equal to 1
Model itself does not save score because it depends on training data. To get score on current training data you can use automl.sprint_statistics() after fitting data.

[mfeurer]

Yep, that's totally corretc @Robotuks

@RaviGprec you can also check a few earlier answers in #721 and #382

I'm closing this for now as the question is answered. Please reopen if you have any further questions on this.