.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "auto_examples/semi_supervised/plot_label_propagation_structure.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code. or to run this example in your browser via Binder .. rst-class:: sphx-glr-example-title .. _sphx_glr_auto_examples_semi_supervised_plot_label_propagation_structure.py: ============================================== 标签传播学习复杂结构 ============================================== 标签传播学习复杂内部结构的示例，以展示“流形学习”。外圈应标记为“红色”，内圈应标记为“蓝色”。由于两个标签组都位于各自的独特形状内，我们可以看到标签在圆周围正确传播。 .. GENERATED FROM PYTHON SOURCE LINES 9-13 .. code-block:: Python # 作者：scikit-learn 开发者 # SPDX许可证标识符：BSD-3-Clause .. GENERATED FROM PYTHON SOURCE LINES 14-15 我们生成了一个包含两个同心圆的数据集。此外，每个数据集样本都关联了一个标签：0（属于外圆），1（属于内圆），以及-1（未知）。在这里，除了两个标签外，所有标签都被标记为未知。 .. GENERATED FROM PYTHON SOURCE LINES 15-28 .. code-block:: Python import numpy as np from sklearn.datasets import make_circles n_samples = 200 X, y = make_circles(n_samples=n_samples, shuffle=False) outer, inner = 0, 1 labels = np.full(n_samples, -1.0) labels[0] = outer labels[-1] = inner .. GENERATED FROM PYTHON SOURCE LINES 29-30 绘制原始数据 .. GENERATED FROM PYTHON SOURCE LINES 30-61 .. code-block:: Python import matplotlib.pyplot as plt plt.figure(figsize=(4, 4)) plt.scatter( X[labels == outer, 0], X[labels == outer, 1], color="navy", marker="s", lw=0, label="outer labeled", s=10, ) plt.scatter( X[labels == inner, 0], X[labels == inner, 1], color="c", marker="s", lw=0, label="inner labeled", s=10, ) plt.scatter( X[labels == -1, 0], X[labels == -1, 1], color="darkorange", marker=".", label="unlabeled", ) plt.legend(scatterpoints=1, shadow=False, loc="center") _ = plt.title("Raw data (2 classes=outer and inner)") .. image-sg:: /auto_examples/semi_supervised/images/sphx_glr_plot_label_propagation_structure_001.png :alt: Raw data (2 classes=outer and inner) :srcset: /auto_examples/semi_supervised/images/sphx_glr_plot_label_propagation_structure_001.png :class: sphx-glr-single-img .. GENERATED FROM PYTHON SOURCE LINES 62-63 :class:`~sklearn.semi_supervised.LabelSpreading` 的目的是为最初标签未知的样本分配标签。 .. GENERATED FROM PYTHON SOURCE LINES 64-69 .. code-block:: Python from sklearn.semi_supervised import LabelSpreading label_spread = LabelSpreading(kernel="knn", alpha=0.8) label_spread.fit(X, labels) .. raw:: html

LabelSpreading(alpha=0.8, kernel='knn')

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.. GENERATED FROM PYTHON SOURCE LINES 70-71 现在，我们可以检查在标签未知时每个样本被关联了哪些标签。 .. GENERATED FROM PYTHON SOURCE LINES 71-99 .. code-block:: Python output_labels = label_spread.transduction_ output_label_array = np.asarray(output_labels) outer_numbers = np.where(output_label_array == outer)[0] inner_numbers = np.where(output_label_array == inner)[0] plt.figure(figsize=(4, 4)) plt.scatter( X[outer_numbers, 0], X[outer_numbers, 1], color="navy", marker="s", lw=0, s=10, label="outer learned", ) plt.scatter( X[inner_numbers, 0], X[inner_numbers, 1], color="c", marker="s", lw=0, s=10, label="inner learned", ) plt.legend(scatterpoints=1, shadow=False, loc="center") plt.title("Labels learned with Label Spreading (KNN)") plt.show() .. image-sg:: /auto_examples/semi_supervised/images/sphx_glr_plot_label_propagation_structure_002.png :alt: Labels learned with Label Spreading (KNN) :srcset: /auto_examples/semi_supervised/images/sphx_glr_plot_label_propagation_structure_002.png :class: sphx-glr-single-img .. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 0.071 seconds) .. _sphx_glr_download_auto_examples_semi_supervised_plot_label_propagation_structure.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: binder-badge .. image:: images/binder_badge_logo.svg :target: https://mybinder.org/v2/gh/scikit-learn/scikit-learn/main?urlpath=lab/tree/notebooks/auto_examples/semi_supervised/plot_label_propagation_structure.ipynb :alt: Launch binder :width: 150 px .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_label_propagation_structure.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_label_propagation_structure.py ` .. container:: sphx-glr-download sphx-glr-download-zip :download:`Download zipped: plot_label_propagation_structure.zip ` .. include:: plot_label_propagation_structure.recommendations .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_