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  1. 6.8. Pairwise metrics, Affinities and Kernels —...

    c ) <= d ( a , b ) + d ( b , c ), the triangle...d(a, b) such that d(a, b) < d(a, c) if objects a and b are considered...
    scikit-learn.org/stable/modules/metrics.html
    Wed Oct 30 20:01:21 UTC 2024
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  2. 1.9. Naive Bayes — scikit-learn 1.5.2 documenta...

    to class \(c\) , \(N_{c} = |\{ j \in J\mid y_j = c\}|\) is the...\sum_{j:y_j \neq c} d_{ij}} {\alpha + \sum_{j:y_j \neq c} \sum_{k} d_{kj}}\\w_{ci}...
    scikit-learn.org/stable/modules/naive_bayes.html
    Wed Oct 30 20:01:23 UTC 2024
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  3. L1 Penalty and Sparsity in Logistic Regression ...

    different values of C. We can see that large values of C give more freedom...coefficients of the models for varying C. C=1.00 Sparsity with L1 penalty:...
    scikit-learn.org/stable/auto_examples/linear_model/plot_logistic_l1_l2_sparsity.html
    Wed Oct 30 20:01:21 UTC 2024
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  4. Plot multi-class SGD on the iris dataset — scik...

    x0 * coef [ c , 0 ]) - intercept [ c ]) / coef [ c , 1 ] plt ....X [ idx , 0 ], X [ idx , 1 ], c = color , label = iris . target_names...
    scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_iris.html
    Wed Oct 30 20:01:21 UTC 2024
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  5. Plot multinomial and One-vs-Rest Logistic Regre...

    x0 * coef [ c , 0 ]) - intercept [ c ]) / coef [ c , 1 ] plt ....X [ idx , 0 ], X [ idx , 1 ], c = color , edgecolor = "black"...
    scikit-learn.org/stable/auto_examples/linear_model/plot_logistic_multinomial.html
    Wed Oct 30 20:01:21 UTC 2024
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  6. Swiss Roll And Swiss-Hole Reduction — scikit-le...

    c = sr_color , s = 50 , alpha =...sr_lle [:, 0 ], sr_lle [:, 1 ], c = sr_color ) axs [ 0 ] . set_title...
    scikit-learn.org/stable/auto_examples/manifold/plot_swissroll.html
    Wed Oct 30 20:01:23 UTC 2024
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  7. Installing scikit-learn — scikit-learn 1.5.2 do...

    for instance: C : \ Users \ username > C : \ Users \ username...packages in the environment python -c "import sklearn; sklearn.show_versions()"...
    scikit-learn.org/stable/install.html
    Wed Oct 30 20:01:23 UTC 2024
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  8. Comparing random forests and the multi-output m...

    c = "c" , s = s , marker = "^" , alpha...y_test [:, 1 ], edgecolor = "k" , c = "navy" , s = s , marker = "s"...
    scikit-learn.org/stable/auto_examples/ensemble/plot_random_forest_regression_multioutput.html
    Wed Oct 30 20:01:21 UTC 2024
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  9. Regularization path of L1- Logistic Regression ...

    coefs_ = [] for c in cs : clf . set_params ( C = c ) clf . fit (...sklearn.svm import l1_min_c cs = l1_min_c ( X , y , loss = "log"...
    scikit-learn.org/stable/auto_examples/linear_model/plot_logistic_path.html
    Wed Oct 30 20:01:23 UTC 2024
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  10. SVM Tie Breaking Example — scikit-learn 1.5.2 d...

    C = 1 , break_ties = break_ties...) pred = svm . predict ( np . c_ [ xx . ravel (), yy . ravel ()])...
    scikit-learn.org/stable/auto_examples/svm/plot_svm_tie_breaking.html
    Wed Oct 30 20:01:21 UTC 2024
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