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  1. A demo of the mean-shift clustering algorithm —...

    colors ): my_members = labels == k cluster_center = cluster_centers...n_samples = 10000 , centers = centers , cluster_std = 0.6 ) Compute...
    scikit-learn.org/stable/auto_examples/cluster/plot_mean_shift.html
    Sat Apr 19 00:31:22 UTC 2025
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  2. Birch — scikit-learn 1.6.1 documentation

    threshold = 0.5 , branching_factor = 50 , n_clusters = 3 , compute_labels...compute_labels = True , copy = 'deprecated' ) [source] # Implements...
    scikit-learn.org/stable/modules/generated/sklearn.cluster.Birch.html
    Sat Apr 19 00:31:20 UTC 2025
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  3. 1.12. Multiclass and multioutput algorithms — s...

    n_informative = 30 , n_classes = 3 , ... random_state = 1 ) >>> y2 = shuffle..., y = datasets . load_iris ( return_X_y = True ) >>> clf = OutputCodeClassifier...
    scikit-learn.org/stable/modules/multiclass.html
    Sat Apr 19 00:31:21 UTC 2025
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  4. Factor Analysis (with rotation) to visualize pa...

    cmap = "RdBu_r" , vmin =- 1 , vmax = 1 ) ax . set_xticks...ncols = len ( methods ), figsize = ( 10 , 8 ), sharey = True )...
    scikit-learn.org/stable/auto_examples/decomposition/plot_varimax_fa.html
    Sat Apr 19 00:31:20 UTC 2025
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  5. LassoLars — scikit-learn 1.6.1 documentation

    copy_X = True , fit_path = True , positive = False , jitter = None...( alpha = 1.0 , * , fit_intercept = True , verbose = False ,...
    scikit-learn.org/stable/modules/generated/sklearn.linear_model.LassoLars.html
    Sat Apr 19 00:31:22 UTC 2025
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  6. Gradient Boosting regression — scikit-learn 1.6...

    n_repeats = 10 , random_state = 42 , n_jobs = 2 ) sorted_idx = result...data. diabetes = datasets . load_diabetes () X , y = diabetes . data...
    scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_regression.html
    Sat Apr 19 00:31:22 UTC 2025
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  7. ハンズオンセクション 4 | DBFlute

    ; map: {code=1; name=True ; alias=はい ; comment=有効を示す} ; map:...map: {code=0; name=False; alias=いいえ; comment=無効を示す} } ; MemberStatus...
    dbflute.seasar.org/ja/tutorial/handson/section04.html
    Fri Apr 18 17:54:33 UTC 2025
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  8. InputTags — scikit-learn 1.6.1 documentation

    bool = False , sparse : bool = False , categorical : bool = False...bool = False , dict : bool = False , positive_only : bool = False...
    scikit-learn.org/stable/modules/generated/sklearn.utils.InputTags.html
    Sat Apr 19 00:31:22 UTC 2025
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  9. LabelPropagation — scikit-learn 1.6.1 documenta...

    LabelPropagation ( kernel = 'rbf' , * , gamma = 20 , n_neighbors = 7 , max_iter...max_iter = 1000 , tol = 0.001 , n_jobs = None ) [source] # Label Propagation...
    scikit-learn.org/stable/modules/generated/sklearn.semi_supervised.LabelPropagation.html
    Sat Apr 19 00:31:21 UTC 2025
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  10. DecisionTreeRegressor — scikit-learn 1.6.1 docu...

    criterion = 'squared_error' , splitter = 'best' , max_depth = None...min_weight_fraction_leaf = 0.0 , max_features = None , random_state = None , max_leaf_nodes...
    scikit-learn.org/stable/modules/generated/sklearn.tree.DecisionTreeRegressor.html
    Sat Apr 19 00:31:22 UTC 2025
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