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Demo of DBSCAN clustering algorithm — scikit-le...
DBSCAN (Density-Based Spatial Clustering of Applications with Noise) finds core samples in regions of high density and expands clusters from them. This algorithm is good for data which contains clu...scikit-learn.org/stable/auto_examples/cluster/plot_dbscan.html -
FastICA on 2D point clouds — scikit-learn 1.8.0...
This example illustrates visually in the feature space a comparison by results using two different component analysis techniques. Independent component analysis (ICA) vs Principal component analysi...scikit-learn.org/stable/auto_examples/decomposition/plot_ica_vs_pca.html -
Spectral clustering for image segmentation — sc...
In this example, an image with connected circles is generated and spectral clustering is used to separate the circles. In these settings, the Spectral clustering approach solves the problem know as...scikit-learn.org/stable/auto_examples/cluster/plot_segmentation_toy.html -
Comparing Linear Bayesian Regressors — scikit-l...
This example compares two different bayesian regressors: an Automatic Relevance Determination - ARD, a Bayesian Ridge Regression. In the first part, we use an Ordinary Least Squares(OLS) model as a...scikit-learn.org/stable/auto_examples/linear_model/plot_ard.html -
OOB Errors for Random Forests — scikit-learn 1....
The RandomForestClassifier is trained using bootstrap aggregation, where each new tree is fit from a bootstrap sample of the training observations z_i = (x_i, y_i). The out-of-bag(OOB) error is the...scikit-learn.org/stable/auto_examples/ensemble/plot_ensemble_oob.html -
Plot Hierarchical Clustering Dendrogram — sciki...
This example plots the corresponding dendrogram of a hierarchical clustering using AgglomerativeClustering and the dendrogram method available in scipy. Total running time of the script:(0 minutes ...scikit-learn.org/stable/auto_examples/cluster/plot_agglomerative_dendrogram.html -
Time-related feature engineering — scikit-learn...
This notebook introduces different strategies to leverage time-related features for a bike sharing demand regression task that is highly dependent on business cycles (days, weeks, months) and yearl...scikit-learn.org/stable/auto_examples/applications/plot_cyclical_feature_engineering.html -
Comparison of Manifold Learning methods — sciki...
An illustration of dimensionality reduction on the S-curve dataset with various manifold learning methods. For a discussion and comparison of these algorithms, see the manifold module page For a si...scikit-learn.org/stable/auto_examples/manifold/plot_compare_methods.html -
Approximate nearest neighbors in TSNE — scikit-...
This example presents how to chain KNeighborsTransformer and TSNE in a pipeline. It also shows how to wrap the packages nmslib and pynndescent to replace KNeighborsTransformer and perform approxima...scikit-learn.org/stable/auto_examples/neighbors/approximate_nearest_neighbors.html -
7.7. Kernel Approximation — scikit-learn 1.8.0 ...
This submodule contains functions that approximate the feature mappings that correspond to certain kernels, as they are used for example in support vector machines (see Support Vector Machines). Th...scikit-learn.org/stable/modules/kernel_approximation.html