random_sample((5, 4)) for kernel in (linear_kernel, polynomial_kernel, rbf_kernel, laplacian_kernel, sigmoid_kernel, cosine_similarity): K = kernel(X, X) assert_array_almost_equal(K, K.T, 15) Example #18Source File: test_pairwise.py From twitter-stock-recommendation with MIT License ...
Hierarchical clustering: structured vs unstructured ward: Example of Ward algorithm on a swiss-roll, comparison of structured approaches versus unstructured approaches. Feature agglomeration vs. univariate selection: Example of dimensionality reduction with feature agglomeration based on Ward hierarchical clusteri...
scikit-learn（简称sklearn）是一个广泛使用的Python机器学习库，它提供了丰富的功能和工具，用于数据挖掘...
The cosine similarity between two vectors (or two documents on the Vector Space) is a measure that calculates the cosine of the angle between them. This metric is a measurement of orientation and not magnitude, it can be seen as a comparison between documents on a normalized space because we...
Scaling inputs to unit norms is a common operation for text classification or clustering for instance. For instance the dot product of two l2-normalized TF-IDF vectors is the cosine similarity of the vectors and is the base similarity metric for the Vector Space Model commonly used by the Inf...
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This is an example showing how the scikit-learn can be used to cluster documents by topics using a bag-of-words approach. This example uses a scipy.sparse matrix to store the features instead of standard numpy arrays. Two feature extraction methods can be used in this example: ...
See the following example with thehandwritten digits data. Here, I visually compare results from the scikit-learn Laplacian Eigenmapsimplementationto those from my implementation. Note that this implementation contains two similarity-learning algorithms:anisotropic diffusion mapsandfuzzy simplicial sets. ...
This page shows the popular functions and classes defined in the sklearn.metrics.pairwise module. The items are ordered by their popularity in 40,000 open source Python projects. If you can not find a good example below, you can try the search function to search modules. ...
cosine_similarity) assert isinstance(sym.metric, types.LambdaType) test_distance = -np.log(skm.cosine_similarity(data[:2,])) comparator = sym.metric(data[:2,]) np.testing.assert_allclose(test_distance, comparator) Example #4Source File: ABuStatsUtil.py From abu with GNU General Public ...