.. note:: :class: sphx-glr-download-link-note Click :ref:`here ` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr_tutorial_auto_examples_usecase_plot_usecase_exampleMumBo.py: ======================= Use Case MumBo on digit ======================= Use case for all classifier of multimodallearn MumBo multi class digit from sklearn, multivue - vue 0 digit data (color of sklearn) - vue 1 gradiant of image in first direction - vue 2 gradiant of image in second direction .. image:: /tutorial/auto_examples/usecase/images/sphx_glr_plot_usecase_exampleMumBo_001.png :class: sphx-glr-single-img .. rst-class:: sphx-glr-script-out Out: .. code-block:: none /home/dominique/.virtualenvs/env_multiv/local/lib/python3.6/site-packages/sklearn/ensemble/weight_boosting.py:29: DeprecationWarning: numpy.core.umath_tests is an internal NumPy module and should not be imported. It will be removed in a future NumPy release. from numpy.core.umath_tests import inner1d result of MumboClassifier on digit 98.22222222222223 /home/dominique/projets/ANR-Lives/scikit-multimodallearn/examples/usecase/plot_usecase_exampleMumBo.py:73: UserWarning: Matplotlib is currently using agg, which is a non-GUI backend, so cannot show the figure. plt.show() | .. code-block:: default import numpy as np import matplotlib.pyplot as plt from sklearn.model_selection import train_test_split from sklearn.tree import DecisionTreeClassifier from multimodal.datasets.base import load_dict, save_dict from multimodal.tests.data.get_dataset_path import get_dataset_path from multimodal.datasets.data_sample import MultiModalArray from multimodal.boosting.mumbo import MumboClassifier import numpy as np import matplotlib.pyplot as plt import matplotlib._color_data as mcd def plot_subplot(X, Y, Y_pred, vue, subplot, title): cn = mcd.CSS4_COLORS classes = np.unique(Y) n_classes = len(np.unique(Y)) axs = plt.subplot(subplot[0],subplot[1],subplot[2]) axs.set_title(title) #plt.scatter(X._extract_view(vue), X._extract_view(vue), s=40, c='gray', # edgecolors=(0, 0, 0)) for index, k in zip(range(n_classes), cn.keys()): Y_class, = np.where(Y==classes[index]) Y_class_pred = np.intersect1d(np.where(Y_pred==classes[index])[0], np.where(Y_pred==Y)[0]) plt.scatter(X._extract_view(vue)[Y_class], X._extract_view(vue)[Y_class], s=40, c=cn[k], edgecolors='blue', linewidths=2, label="class real class: "+str(index)) # plt.scatter(X._extract_view(vue)[Y_class_pred], X._extract_view(vue)[Y_class_pred], s=160, edgecolors='orange', linewidths=2, label="class prediction: "+str(index)) if __name__ == '__main__': # file = get_dataset_path("digit_histogram.npy") file = get_dataset_path("digit_col_grad.npy") y = np.load(get_dataset_path("digit_y.npy")) base_estimator = DecisionTreeClassifier(max_depth=4) dic_digit = load_dict(file) XX =MultiModalArray(dic_digit) X_train, X_test, y_train, y_test = train_test_split(XX, y) est2 = MumboClassifier(base_estimator=base_estimator).fit(X_train, y_train) y_pred2 = est2.predict(X_test) y_pred22 = est2.predict(X_train) print("result of MumboClassifier on digit ") result2 = np.mean(y_pred2.ravel() == y_test.ravel()) * 100 print(result2) fig = plt.figure(figsize=(12., 11.)) fig.suptitle("Mumbo: result" + str(result2), fontsize=16) plot_subplot(X_train, y_train, y_pred22 , 0, (4, 1, 1), "train vue 0" ) plot_subplot(X_test, y_test,y_pred2, 0, (4, 1, 2), "test vue 0" ) plot_subplot(X_test, y_test, y_pred2, 1, (4, 1, 3), "test vue 1" ) plot_subplot(X_test, y_test,y_pred2, 2, (4, 1, 4), "test vue 2" ) # plt.legend() plt.show() .. rst-class:: sphx-glr-timing **Total running time of the script:** ( 0 minutes 6.374 seconds) .. _sphx_glr_download_tutorial_auto_examples_usecase_plot_usecase_exampleMumBo.py: .. only :: html .. container:: sphx-glr-footer :class: sphx-glr-footer-example .. container:: sphx-glr-download :download:`Download Python source code: plot_usecase_exampleMumBo.py ` .. container:: sphx-glr-download :download:`Download Jupyter notebook: plot_usecase_exampleMumBo.ipynb ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_