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LabelPropagation — scikit-learn 1.5.2 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 -
区分値 (Classification) | DBFlute
codeType=String} ; map: {code=PRV;name=Provisional;alias=仮会員 ;c...{code=PRV;name=Provisional;alias=仮会員 ;comment= ... } ; map: {code=FML;name=Formalized...dbflute.seasar.org/ja/manual/function/genbafit/implfit/classification/index.html -
RationalQuadratic — scikit-learn 1.5.2 document...
length_scale = 1.0 , alpha = 1.0 , length_scale_bounds = (1e-05, 100000.0)...>>> X , y = load_iris ( return_X_y = True ) >>> kernel = RationalQuadratic...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.RationalQuadratic.html -
RBF — scikit-learn 1.5.2 documentation
y = load_iris ( return_X_y = True ) >>> kernel = 1.0 * RBF...( length_scale = 1.0 , length_scale_bounds = (1e-05, 100000.0)...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.RBF.html -
The Iris Dataset — scikit-learn 1.5.2 documenta...
projection = "3d" , elev =- 150 , azim = 110 ) X_reduced = PCA ( n_components...PCA fig = plt . figure ( 1 , figsize = ( 8 , 6 )) ax = fig . add_subplot...scikit-learn.org/stable/auto_examples/datasets/plot_iris_dataset.html -
GaussianRandomProjection — scikit-learn 1.5.2 d...
GaussianRandomProjec ( n_components = 'auto' , * , eps = 0.1 , compute_inverse_components...compute_inverse_components = False , random_state = None ) [source] # Reduce...scikit-learn.org/stable/modules/generated/sklearn.random_projection.GaussianRandomProjection.html -
A Guy Who Made A Pass At My Wife Is Back, And M...
fill="none" viewBox="0 0 24 24" stroke-width="1.5" stroke="currentColor">...fill="none" viewBox="0 0 24 24" stroke-width="1.5" stroke="currentColor">...digg.com/relationships/link/best-friend-wants-my-wife-relationship-advice-stories-men-Reddit-roundup -
load_files — scikit-learn 1.5.2 documentation
description = None , categories = None , load_content = True , shuffle...shuffle = True , encoding = None , decode_error = 'strict' , random_state...scikit-learn.org/stable/modules/generated/sklearn.datasets.load_files.html -
r2_score — scikit-learn 1.5.2 documentation
sample_weight = None , multioutput = 'uniform_average' ,...r2_score >>> y_true = [ 3 , - 0.5 , 2 , 7 ] >>> y_pred = [ 2.5 , 0.0...scikit-learn.org/stable/modules/generated/sklearn.metrics.r2_score.html -
RFE — scikit-learn 1.5.2 documentation
n_features_to_select = None , step = 1 , verbose = 0 , importance_getter = 'auto'...X , y = make_friedman1 ( n_samples = 50 , n_features = 10 , random_state...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.RFE.html