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MultiTaskLassoCV — scikit-learn 1.5.2 documenta...
fit_intercept = True , max_iter = 1000 , tol = 0.0001 , copy_X = True...precompute = 'auto' , Xy = None , copy_X = True , coef_init = None...scikit-learn.org/stable/modules/generated/sklearn.linear_model.MultiTaskLassoCV.html -
Model selection with Probabilistic PCA and Fact...
rank = 500 , 25 , 5 sigma = 1.0 rng = np . random ....compute_scores ( X ): pca = PCA ( svd_solver = "full" ) fa = FactorAnalysis...scikit-learn.org/stable/auto_examples/decomposition/plot_pca_vs_fa_model_selection.html -
6.1. Pipelines and composite estimators — sciki...
>>> iris = load_iris () >>> pipe = Pipeline ( steps = [ ... (...memory = cachedir ) >>> pipe Pipeline(memory=..., steps=[('reduce_dim',...scikit-learn.org/stable/modules/compose.html -
alter-step1-check-alterddl.png
17639795 width=2292, height=836, bitDepth=8, colorType=RGBAlpha, ...translatedKeyword=, text=<x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="XMP...dbflute.seasar.org/data/snapshot/intro/alter/alter-step1-check-alterddl.png -
SVM: Separating hyperplane for unbalanced class...
plot_method = "contour" , colors = "k" , levels = [ 0 ], alpha = 0.5...plot_method = "contour" , colors = "r" , levels = [ 0 ], alpha = 0.5...scikit-learn.org/stable/auto_examples/svm/plot_separating_hyperplane_unbalanced.html -
10. Common pitfalls and recommended practices —...
random_state = 42 >>> X , y = make_regression ( random_state = random_state...random_state = 42 ) >>> gbc = GradientBoostingClas ( random_state = 1 )...scikit-learn.org/stable/common_pitfalls.html -
RBF SVM parameters — scikit-learn 1.5.2 documen...
vmin = None , vmax = None , midpoint = None , clip = False ):...param_grid = dict ( gamma = gamma_range , C = C_range ) cv = StratifiedShuffleSpl...scikit-learn.org/stable/auto_examples/svm/plot_rbf_parameters.html -
gen_batches — scikit-learn 1.5.2 documentation
min_batch_size = 0 ) [source] # Generator to create...batch. min_batch_size int, default=0 Minimum number of elements in...scikit-learn.org/stable/modules/generated/sklearn.utils.gen_batches.html -
1. Metadata Routing — scikit-learn 1.5.2 docume...
sample_weight = True ) >>> sel = SelectKBest ( k = 2 ) >>> pipe = make_pipeline...sample_weight = True ) >>> lr = LogisticRegressionCV ( ... cv = GroupKFold...scikit-learn.org/stable/metadata_routing.html -
Faces recognition example using eigenfaces and ...
subplots_adjust ( bottom = 0 , left = 0.01 , right = 0.99 , top = 0.90 , hspace...random_state = 42 ) scaler = StandardScaler () X_train = scaler ....scikit-learn.org/stable/auto_examples/applications/plot_face_recognition.html
