Project
Reverse Dependencies for numo-narray
The projects listed here declare numo-narray as a runtime or development dependency
0.28
Rumale::Clustering provides cluster analysis algorithms,
such as K-Means, Gaussian Mixture Model, DBSCAN, and Spectral Clustering,
with Rumale interface.
2019
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2021
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0.28
Rumale::Core provides base classes and utility functions for implementing
machine learning algorithm with Rumale interface.
2019
2020
2021
2022
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0.26
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, Rando...
2019
2020
2021
2022
2023
2024
0.25
Rumale::Decomposition provides matrix decomposition algorithms,
such as Principal Component Analysis, Non-negative Matrix Factorization, Factor Analysis, and Independent Component Analysis,
with Rumale interface.
2019
2020
2021
2022
2023
2024
0.25
Rumale::Ensemble provides ensemble learning algorithms,
such as AdaBoost, Gradient Tree Boosting, and Random Forest,
with Rumale interface.
2019
2020
2021
2022
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0.25
Rumale::EvaluationMeasure provides evaluation measures,
such as accuracy, precision, recall, and f-score,
with Rumale interface.
2019
2020
2021
2022
2023
2024
0.25
Rumale::FeatureExtraction provides feature extraction methods,
such as TF-IDF and feature hashing,
with Rumale interface.
2019
2020
2021
2022
2023
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0.25
Rumale::KernelApproximation provides kernel approximation algorithms,
such as RBF feature mapping and Nystroem method,
with Rumale interface.
2019
2020
2021
2022
2023
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0.25
Rumale::KernelMachine provides kernel method-based algorithms,
such as Kernel Support Vector Machine, Kernel Principal Componenet Analysis, and Kernel Ridge Regression,
with Rumale interface.
2019
2020
2021
2022
2023
2024
0.25
Rumale::LinearModel provides linear model algorithms,
such as Logistic Regression, Support Vector Machine, Lasso, and Ridge Regression
with Rumale interface.
2019
2020
2021
2022
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2024
0.25
Rumale::Manifold provides data embedding algorithms,
such as Multi-dimensional Scaling, Locally Linear Embedding, Laplacian Eigenmaps, Hessian Eigenmaps,
and t-distributed Stochastic Neighbor Embedding,
with Rumale interface.
2019
2020
2021
2022
2023
2024
0.25
Rumale::MetricLearning provides metric learning algorithms,
such as Fisher Discriminant Analysis and Neighboourhood Component Analysis
with Rumale interface.
2019
2020
2021
2022
2023
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0.25
Rumale::ModelSelection provides model validation techniques,
such as k-fold cross-validation, time series cross-validation, and grid search,
with Rumale interface.
2019
2020
2021
2022
2023
2024
0.25
Rumale::NaiveBayes provides naive bayes models,
such as Gaussian Naive Bayes, Multinomial Naive Bayes, and Bernoulli Naive Bayes,
with Rumale interface.
2019
2020
2021
2022
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0.25
Rumale::NearestNeighbors provides classifier and regression based on nearest neighbors rule with Rumale interface.
2019
2020
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0.25
Rumale::NeuralNetwork provides classifiers and regression algorithms based on multi-layer perceptron,
radial basis function network, and random vector functional link network in the Rumale interface.
2019
2020
2021
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0.25
Rumale::Pipeline provides classes for chaining transformers and estimators with Rumale interface.
2019
2020
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0.25
Rumale::Preprocessing provides preprocessing techniques,
such as L2 normalization, standard scaling, and one-hot encoding,
with Rumale interface.
2019
2020
2021
2022
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0.25
Rumale::Tree provides classifier and regression based on decision tree algorithms with Rumale interface.
2019
2020
2021
2022
2023
2024
0.17
Recommendations for Ruby and Rails using collaborative filtering
2019
2020
2021
2022
2023
2024