neighbors.NearestNeighbors()
  • References/Python/scikit-learn/API Reference/neighbors

class sklearn.neighbors.NearestNeighbors(n_neighbors=5, radius=1.0, algorithm='auto', leaf_size=30, metric='minkowski', p=2, metric_params=None

2025-01-10 15:47:30
sklearn.datasets.load_iris()
  • References/Python/scikit-learn/API Reference/datasets

sklearn.datasets.load_iris(return_X_y=False)

2025-01-10 15:47:30
decomposition.NMF()
  • References/Python/scikit-learn/API Reference/decomposition

class sklearn.decomposition.NMF(n_components=None, init=None, solver='cd', tol=0.0001, max_iter=200, random_state=None, alpha=0.0, l1_ratio=0

2025-01-10 15:47:30
base.BaseEstimator
  • References/Python/scikit-learn/API Reference/base

class sklearn.base.BaseEstimator

2025-01-10 15:47:30
sklearn.model_selection.cross_val_predict()
  • References/Python/scikit-learn/API Reference/model_selection

sklearn.model_selection.cross_val_predict(estimator, X, y=None, groups=None, cv=None, n_jobs=1, verbose=0, fit_params=None

2025-01-10 15:47:30
feature_selection.SelectPercentile()
  • References/Python/scikit-learn/API Reference/feature_selection

class sklearn.feature_selection.SelectPercentile(score_func=, percentile=10)

2025-01-10 15:47:30
kernel_approximation.SkewedChi2Sampler()
  • References/Python/scikit-learn/API Reference/kernel_approximation

class sklearn.kernel_approximation.SkewedChi2Sampler(skewedness=1.0, n_components=100, random_state=None)

2025-01-10 15:47:30
sklearn.metrics.zero_one_loss()
  • References/Python/scikit-learn/API Reference/metrics

sklearn.metrics.zero_one_loss(y_true, y_pred, normalize=True, sample_weight=None)

2025-01-10 15:47:30
base.ClassifierMixin
  • References/Python/scikit-learn/API Reference/base

class sklearn.base.ClassifierMixin

2025-01-10 15:47:30