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Label Propagation digits: Demonstrating perform...
This example demonstrates the power of semisupervised learning by training a Label Spreading model to classify handwritten digits with sets of very few labels. The handwritten digit dataset has 179...scikit-learn.org/stable/auto_examples/semi_supervised/plot_label_propagation_digits.html -
Label Propagation digits: Active learning — sci...
Demonstrates an active learning technique to learn handwritten digits using label propagation. We start by training a label propagation model with only 10 labeled points, then we select the top fiv...scikit-learn.org/stable/auto_examples/semi_supervised/plot_label_propagation_digits_active_learni... -
SVM: Maximum margin separating hyperplane — sci...
Plot the maximum margin separating hyperplane within a two-class separable dataset using a Support Vector Machine classifier with linear kernel. Total running time of the script:(0 minutes 0.053 se...scikit-learn.org/stable/auto_examples/svm/plot_separating_hyperplane.html -
7.4. Imputation of missing values — scikit-lear...
For various reasons, many real world datasets contain missing values, often encoded as blanks, NaNs or other placeholders. Such datasets however are incompatible with scikit-learn estimators which ...scikit-learn.org/stable/modules/impute.html -
1.3. Kernel ridge regression — scikit-learn 1.8...
Kernel ridge regression (KRR)[M2012] combines Ridge regression and classification(linear least squares with L_2-norm regularization) with the kernel trick. It thus learns a linear function in the s...scikit-learn.org/stable/modules/kernel_ridge.html -
Illustration of prior and posterior Gaussian pr...
This example illustrates the prior and posterior of a GaussianProcessRegressor with different kernels. Mean, standard deviation, and 5 samples are shown for both prior and posterior distributions. ...scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpr_prior_posterior.html -
Single estimator versus bagging: bias-variance ...
This example illustrates and compares the bias-variance decomposition of the expected mean squared error of a single estimator against a bagging ensemble. In regression, the expected mean squared e...scikit-learn.org/stable/auto_examples/ensemble/plot_bias_variance.html -
Compressive sensing: tomography reconstruction ...
This example shows the reconstruction of an image from a set of parallel projections, acquired along different angles. Such a dataset is acquired in computed tomography(CT). Without any prior infor...scikit-learn.org/stable/auto_examples/applications/plot_tomography_l1_reconstruction.html -
Principal Component Analysis (PCA) on Iris Data...
This example shows a well known decomposition technique known as Principal Component Analysis (PCA) on the Iris dataset. This dataset is made of 4 features: sepal length, sepal width, petal length,...scikit-learn.org/stable/auto_examples/decomposition/plot_pca_iris.html -
Probabilistic predictions with Gaussian process...
This example illustrates the predicted probability of GPC for an RBF kernel with different choices of the hyperparameters. The first figure shows the predicted probability of GPC with arbitrarily c...scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpc.html