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l1_min_c — scikit-learn 1.7.2 documentation
'squared_hinge' , fit_intercept = True ) : .4f } " ) 0.0044 Gallery examples...l1_min_c ( X , y , * , loss = 'squared_hinge' , fit_intercept = True...scikit-learn.org/stable/modules/generated/sklearn.svm.l1_min_c.html -
2.6. Covariance estimation — scikit-learn 1.7.2...
distributed (i.i.d.). 2.6.1. Empirical covariance # The covariance...object to data. 2.6.2. Shrunk Covariance # 2.6.2.1. Basic shrinkage...scikit-learn.org/stable/modules/covariance.html -
9.1. Strategies to scale computationally: bigge...
algorithm 9.1.1.1. Streaming instances # Basically, 1. may be a...documents. 9.1.1.3. Incremental learning # Finally, for 3. we have...scikit-learn.org/stable/computing/scaling_strategies.html -
1.14. Semi-supervised learning — scikit-learn 1...
gamma. knn ( \(1[x' \in kNN(x)]\) ). \(k\) is specified by keyword...|x-y|^2), \gamma > 0\) ). \(\gamma\) is specified by keyword gamma....scikit-learn.org/stable/modules/semi_supervised.html -
9.2. Computational Performance — scikit-learn 1...
or one-at-a-time mode. 9.2.1.1. Bulk versus Atomic mode # In general...sparsity_ratio ( X ): return 1.0 - np . count_nonzero ( X ) / float ( X ....scikit-learn.org/stable/computing/computational_performance.html -
MultiTaskLasso — scikit-learn 1.7.2 documentation
], [ 1 , 2 ], [ 2 , 4 ]], [[ 0 , 0 ], [ 1 , 1 ], [ 2 , 3 ]]) ...MultiTaskLasso(alpha=0.1) >>> print ( clf . coef_ ) [[0. 0.60809415]...scikit-learn.org/stable/modules/generated/sklearn.linear_model.MultiTaskLasso.html -
2.9. Neural network models (unsupervised) — sci...
belief nets” , G. Hinton, S. Osindero, Y.-W. Teh, 2006 “Training...= \frac{1}{1 + e^{-x}}\] 2.9.1.3. Stochastic Maximum Likelihood...scikit-learn.org/stable/modules/neural_networks_unsupervised.html -
3.5. Validation curves: plotting scores to eval...
0.9 , 0.96, 0.9 ], [0.9, 0.83, 0.96, 0.96, 0.93], [1. , 0.93,...0.94, 0.91, 0.89, 0.92], [0.9 , 0.92, 0.93, 0.92, 0.93], [0.97, 1...scikit-learn.org/stable/modules/learning_curve.html -
3.3. Tuning the decision threshold for class pr...
, 0.06 ], [0.0416, 0.9583], [0.0416, 0.9583]]) >>> classifier...make_classification ( ... n_samples = 1_000 , weights = [ 0.1 , 0.9 ], random_state...scikit-learn.org/stable/modules/classification_threshold.html -
7.6. Random Projection — scikit-learn 1.7.2 doc...
mining (KDD ‘01). ACM, New York, NY, USA, 245-250. 7.6.1. The ...im ( n_samples = 1e6 , eps = [ 0.5 , 0.1 , 0.01 ]) array([ 663,...scikit-learn.org/stable/modules/random_projection.html