dimensionality-reduction
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Following up on the discussion here, it would be good to document how to get reproducible results with UMAP.
I think we should consider changing random_state in the UMAP constructor to a seed (e.g. 42, like the new transform_seed default) so that UMAP is reproducible by default.
We should document that users can set `ran
Community-curated list of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc.
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Jan 27, 2020
A curated list of community detection research papers with implementations.
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Jan 24, 2020 - Python
Text Classification Algorithms: A Survey
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Jan 24, 2020 - Python
A high-level machine learning and deep learning library for the PHP language.
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Jan 24, 2020 - PHP
Extensible, parallel implementations of t-SNE
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Jan 24, 2020 - Python
:red_circle: MiniSom is a minimalistic implementation of the Self Organizing Maps
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Jan 26, 2020 - Python
Using siamese network to do dimensionality reduction and similar image retrieval
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Jan 19, 2020 - Jupyter Notebook
@sirusb, @ttriche: as contributors of PRs to this package, would you like to be acknowledged as such in the Authors@R field of the DESCRIPTION? You don't need to provide an email address, just a suitable identifier, e.g. first name and last name. For reference, the field currently looks like:
c(person("James", "Melville", email = "jlmelville@gmail.com", role = c("aut", "cre")),
Dimensionality reduction in very large datasets using Siamese Networks
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Jan 25, 2020 - Python
Unless I'm missing something, the implementation (and docs) of llsq don't agree with the statement on the documentation index that data matrices have features as rows and observations as columns.
In the following code from the llsq documentation, the number of observations is 1000, and the number of features is 3, but the observation matrix X has 1000 rows and 3 columns, and the output fr
A sparsity aware implementation of "Deep Autoencoder-like Nonnegative Matrix Factorization for Community Detection" (CIKM 2018).
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Jan 24, 2020 - Python
It would be nice if it supports Thin Plate Spline (TPS) interpolation.
Machine Learning notebooks for refreshing concepts.
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Jan 14, 2020 - Jupyter Notebook
[Under development]- Implementation of various methods for dimensionality reduction and spectral clustering implemented with Pytorch
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Dec 31, 2019 - Python
A repository of pretty cool datasets that I collected for network science and machine learning research.
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Jan 24, 2020
JavaScript implementation of UMAP
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Jan 24, 2020 - JavaScript
t-Distributed Stochastic Neighbor Embedding (t-SNE) in Go
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Jan 13, 2020 - Go
The doctstring for _randomized_dpca says that it returns P, encoding matrices used to transform data, and D, decoding matrices used to inverse transform data.
However, the actual implementation of transform(X) uses D and the [implement
Apparently, the absolute path of the Travis build is used (/home/travis/...) instead of the relative path to the current page.
For example, Fs Peptide (in RAM) links (in the bottom) to [this page](http://msmbuilder.org/home/travis/build/msmbuilder/msmbuilder/docs/_build/html/examples/Fs-Peptide-in-RAM/Fs-Peptide-in-RAM.ipynb
Uniform Manifold Approximation and Projection - R package
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Jan 24, 2020 - R
Codes and Project for Machine Learning Course, Fall 2018, University of Tabriz
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Jan 22, 2020 - Jupyter Notebook
For discrete data like spikes the transform function that maps the data into the aligned space can smear out the spikes in time, leading to continuous values. We should add an option to either round spikes to the nearest bin, or return the continuous times of the spikes in the aligned space.
Similarity Weighted Nonnegative Embedding (SWNE), a method for visualizing high dimensional datasets
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Dec 19, 2019 - R
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i'm a newbie in programming. I try to use this library. it's very useful for me.
I want to show centroid in K-means clustering. how to show it? thank u so much..