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0.0
Provides the basic functionality to interact with the Collatz conjecture.
The parameterisation uses the same (P,a,b) notation as Conway's generalisations.
Besides the function and reverse function, there is also functionality to retrieve
the hailstone sequence, the "stopping time"/"total stopping time", or tree-graph.
The only restriction placed on parameters is that both P and a can't be 0.
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Activity
0.0
tree command for rspec test files.
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0.0
Trees, Heaps, Timers, Error fitting, etc
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0.0
DSL for building trees
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0.0
Extracting the contents of Microsoft Windows Registry (hive) and display it as a colorful tree but mainly focused on parsing BCD files to extract WIM files path for PXE attacks.
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Activity
0.02
Ruby bindings for Tree-Sitter
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Activity
0.0
Tools to manipulate DRUID trees and content directories
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Activity
0.01
This is a syntax highlighter plugin for Kramdown that leverages Tree-sitter's native syntax highlighter to highlight code blocks (and spans) when rendering HTML.
Tree-sitter is a modern, general-purpose parsing library that outclasses many existing tools at the task of syntax highlighting. This plugin adapts Tree-sitter's native highlighter for Kramdown, so that Tree-sitter's superior highlighting capabilities can be easily leveraged in the context of rendering Markdown.
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Activity
0.03
Syntax Tree support for RBS
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Activity
0.45
A parser based on ripper
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Activity
0.0
A syntax_tree plugin to disable int formatting.
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0.0
Christmas tree cli
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0.25
Rumale is a machine learning library in Ruby.
Rumale provides machine learning algorithms with interfaces similar to Scikit-Learn in Python.
Rumale supports Support Vector Machine,
Logistic Regression, Ridge, Lasso,
Multi-layer Perceptron,
Naive Bayes, Decision Tree, Gradient Tree Boosting, Random Forest,
K-Means, Gaussian Mixture Model, DBSCAN, Spectral Clustering,
Mutidimensional Scaling, t-SNE,
Fisher Discriminant Analysis, Neighbourhood Component Analysis,
Principal Component Analysis, Non-negative Matrix Factorization,
and many other algorithms.
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0.25
Rumale::Ensemble provides ensemble learning algorithms,
such as AdaBoost, Gradient Tree Boosting, and Random Forest,
with Rumale interface.
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0.25
SVMKit is a machine learninig library in Ruby.
SVMKit provides machine learning algorithms with interfaces similar to Scikit-Learn in Python.
SVMKit supports Linear / Kernel Support Vector Machine,
Logistic Regression, Linear Regression, Ridge, Lasso, Factorization Machine,
Naive Bayes, Decision Tree, AdaBoost, Random Forest, K-nearest neighbor algorithm,
K-Means, DBSCAN, Principal Component Analysis, and Non-negative Matrix Factorization.
Note that the SVMKit has been deprecated and has been renamed to Rumale.
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0.25
Rumale::Tree provides classifier and regression based on decision tree algorithms with Rumale interface.
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Activity
Routing tree web toolkit
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Activity
0.0
hierarchy-tree is a gem that shows the whole hierarchy
and the associations related to a desired class.
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Activity
0.14
This gem facilitates modeling a test suite that is written in Gherkin (e.g. Cucumber, SpecFlow, Lettuce, etc.). It does this by providing an abstraction layer on top of the Abstract Syntax Tree that the 'cucumber-gherkin' gem generates when parsing features, as well as providing models for feature files and directories in order to be able to have a fully traversable model tree of a test suite's structure. These models can then be analyzed or manipulated more easily than the underlying AST layer.
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0.0
A collection of Stern-Brocot based models and methods
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