- Sort Score
- Num 10 results
- Language All
- Labels All
Results 971 - 980 of 3,496 for document (4.27 seconds)
-
7.6. Random Projection — scikit-learn 1.8...
The sklearn.random_projection module implements a simple and computationally efficient way to reduce the dimensionality of the data by trading a controlled amount of accuracy (as additional varianc...scikit-learn.org/stable/modules/random_projection.html -
Demo of HDBSCAN clustering algorithm — sc...
In this demo we will take a look at cluster.HDBSCAN from the perspective of generalizing the cluster.DBSCAN algorithm. We’ll compare both algorithms on specific datasets. Finally we’ll evaluate HDB...scikit-learn.org/stable/auto_examples/cluster/plot_hdbscan.html -
Recognizing hand-written digits — scikit-...
This example shows how scikit-learn can be used to recognize images of hand-written digits, from 0-9. Digits dataset: The digits dataset consists of 8x8 pixel images of digits. The images attribute...scikit-learn.org/stable/auto_examples/classification/plot_digits_classification.html -
Sparse coding with a precomputed dictionary ...
Transform a signal as a sparse combination of Ricker wavelets. This example visually compares different sparse coding methods using the SparseCoder estimator. The Ricker (also known as Mexican hat ...scikit-learn.org/stable/auto_examples/decomposition/plot_sparse_coding.html -
Density Estimation for a Gaussian mixture ̵...
Plot the density estimation of a mixture of two Gaussians. Data is generated from two Gaussians with different centers and covariance matrices. Total running time of the script:(0 minutes 0.121 sec...scikit-learn.org/stable/auto_examples/mixture/plot_gmm_pdf.html -
Lasso on dense and sparse data — scikit-l...
We show that linear_model.Lasso provides the same results for dense and sparse data and that in the case of sparse data the speed is improved. Comparing the two Lasso implementations on Dense data:...scikit-learn.org/stable/auto_examples/linear_model/plot_lasso_dense_vs_sparse_data.html -
Map data to a normal distribution — sciki...
This example demonstrates the use of the Box-Cox and Yeo-Johnson transforms through PowerTransformer to map data from various distributions to a normal distribution. The power transform is useful a...scikit-learn.org/stable/auto_examples/preprocessing/plot_map_data_to_normal.html -
Neighborhood Components Analysis Illustration &...
This example illustrates a learned distance metric that maximizes the nearest neighbors classification accuracy. It provides a visual representation of this metric compared to the original point sp...scikit-learn.org/stable/auto_examples/neighbors/plot_nca_illustration.html -
scikit-learn: machine learning in Python —...
Skip to main content Back to top Ctrl + K scikit-learn Machine Learning in Python Getting Started Release Highlights ...scikit-learn.org/stable/index.html -
14. External Resources, Videos and Talks —...
The scikit-learn MOOC: If you are new to scikit-learn, or looking to strengthen your understanding, we highly recommend the scikit-learn MOOC (Massive Open Online Course). The MOOC, created and mai...scikit-learn.org/stable/presentations.html