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model_evaluation.rst.txt
labeling1 = [2, 0, 2, 2, 0, 1] >>> labeling2 = [0, 0, 2, 2, 0, 2] >>>...y_true = [2, 0, 2, 2, 0, 1] >>> y_pred = [0, 0, 2, 2, 0, 2] >>> ...scikit-learn.org/stable/_sources/modules/model_evaluation.rst.txt -
RepeatedKFold — scikit-learn 1.6.0 documentation
2 ], [ 3 , 4 ], [ 1 , 2 ], [ 3 , 4 ]]) >>>...RepeatedKFold ( n_splits = 2 , n_repeats = 2 , random_state = 2652124...scikit-learn.org/stable/modules/generated/sklearn.model_selection.RepeatedKFold.html -
classification_report — scikit-learn 1.7.dev0 d...
2 , 2 , 2 ] >>> y_pred = [ 0 , 0 , 2 , 2 , 1 ] >>>...sample_weight = None , digits = 2 , output_dict = False , zero_division...scikit-learn.org/dev/modules/generated/sklearn.metrics.classification_report.html -
1.1. Linear Models — scikit-learn 1.6.0 documen...
x_1 + w_2 x_2 + w_3 x_1 x_2 + w_4 x_1^2 + w_5 x_2^2\] The (sometimes...\([x_1, x_2]\) to \([1, x_1, x_2, x_1^2, x_1 x_2, x_2^2]\) , and...scikit-learn.org/stable/modules/linear_model.html -
風の電話 | MetaFilter
}(); </script> 風の電話 December 2, 2024 2:38 PM Subscribe "The wind...Death .' posted by clavdivs (2 comments total) 8 users marked...www.metafilter.com/206545/ -
All podcasts lead to Rome. | MetaFilter
Justinian at 4:54 PM on January 2, 2009 [ 2 favorites ] This is cool....blue_beetle at 5:29 PM on January 2, 2009 [ 2 favorites ] I may have to...www.metafilter.com/77925/All-podcasts-lead-to-Rome -
Understanding optimized scalar quantization - E...
x ∥ 2 = ∥ x ∥ 2 + ∥ y ∥ 2 − 2 x t y \|y-x\|^2 = \|x\|^2 + \|y\|^2...) = 1 2 π ∫ x ( t − c ) 2 e − t 2 / 2 d t = 1 2 ( c 2 + 1 ) erf...www.elastic.co/search-labs/blog/scalar-quantization-optimization -
RegressorMixin — scikit-learn 1.7.dev0 document...
2 ], [ 2 , 3 ], [ 3 , 4 ]]) >>> y =...float \(R^2\) of self.predict(X) w.r.t. y . Notes The \(R^2\) score...scikit-learn.org/dev/modules/generated/sklearn.base.RegressorMixin.html -
feature_extraction.rst.txt
2.0986]}{\sqrt{\big(3^2 + 0^2 + 2.0986^2\big)}} = [...\frac{v}{||v||_2} = \frac{v}{\sqrt{v{_1}^2 + v{_2}^2 + \dots + v{_n}^2}}`....scikit-learn.org/stable/_sources/modules/feature_extraction.rst.txt -
TimeSeriesSplit — scikit-learn 1.6.0 documentation
2 ], [ 3 , 4 ], [ 1 , 2 ], [ 3 , 4 ], [ 1 , 2 ], [ 3 ,...1] Test: index=[2] Fold 2: Train: index=[0 1 2] Test: index=[3]...scikit-learn.org/stable/modules/generated/sklearn.model_selection.TimeSeriesSplit.html