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6. Visualizations — scikit-learn 1.7.1 document...
y = load_iris ( return_X_y = True ) y = y == 2 # make...load_iris X , y = load_iris ( return_X_y = True ) y = y == 2 # make...scikit-learn.org/stable/visualizations.html -
SGDOneClassSVM — scikit-learn 1.7.1 documentation
nu = 0.5 , fit_intercept = True , max_iter = 1000 , tol = 0.001...0.001 , shuffle = True , verbose = 0 , random_state = None , learning_rate...scikit-learn.org/stable/modules/generated/sklearn.linear_model.SGDOneClassSVM.html -
type_of_target — scikit-learn 1.7.1 documentation
input_name = '' , raise_unknown = False ) [source] #...matrix. input_name str, default=”” The data name used to construct...scikit-learn.org/stable/modules/generated/sklearn.utils.multiclass.type_of_target.html -
make_classification — scikit-learn 1.7.1 docume...
n_clusters_per_class = 2 , weights = None , flip_y = 0.01 , class_sep = 1.0 ,...hypercube = True , shift = 0.0 , scale = 1.0 , shuffle = True ,...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_classification.html -
BaggingRegressor — scikit-learn 1.7.1 documenta...
n_informative = 2 , n_targets = 1 , ... random_state = 0 , shuffle = False...estimator = None , n_estimators = 10 , * , max_samples = 1.0 , max_features...scikit-learn.org/stable/modules/generated/sklearn.ensemble.BaggingRegressor.html -
RandomForestClassifier — scikit-learn 1.7.1 doc...
n_estimators = 100 , * , criterion = 'gini' , max_depth = None , min_samples_split...min_weight_fraction_leaf = 0.0 , max_features = 'sqrt' , max_leaf_nodes = None ,...scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html -
Debugging Azure Networking for Elastic Cloud Se...
ENV{INTERFACE}=="en*", ENV{ID_NET_DRIVER}=="mlx5_core", RUN+="/sbin/ethtool...--colors=java --hash --title=aks-k8s-node-1 --width=1440 --minwidth=0.005...www.elastic.co/observability-labs/blog/debugging-aks-packet-loss -
Plot the decision surface of decision trees tra...
Parameters n_classes = 3 plot_colors = "ryb" plot_step = 0.02 for pairidx...tight_layout ( h_pad = 0.5 , w_pad = 0.5 , pad = 2.5 ) DecisionBoundaryDisp...scikit-learn.org/stable/auto_examples/tree/plot_iris_dtc.html -
RandomTreesEmbedding — scikit-learn 1.7.1 docum...
n_estimators = 100 , * , max_depth = 5 , min_samples_split = 2 , min_samples_leaf...max_leaf_nodes = None , min_impurity_decrease = 0.0 , sparse_output = True...scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomTreesEmbedding.html -
Feature agglomeration — scikit-learn 1.7.1 docu...
( left = 0.01 , right = 0.99 , bottom = 0.01 , top = 0.91 ) for...], cmap = plt . cm . gray , vmax = 16 , interpolation = "nearest"...scikit-learn.org/stable/auto_examples/cluster/plot_digits_agglomeration.html