chore: initial commit after reboot

.gitignore

@@ -1,25 +1,19 @@
-/.bundle/
-/.yardoc
-/Gemfile.lock
-/yarn.lock
-/_yardoc/
-/coverage/
-/doc/
-/pkg/
-/spec/reports/
-/tmp/
-/node_modules/
+.bundle/
+.yardoc
+_yardoc/
+coverage/
+doc/
+node_modules/
+pkg/
+tmp/
 
-# rspec failure tracking
-.rspec_status
-
-*.swp
 *.bundle
-tags
+*.so
+*.o
+*.a
+*.log
+*.swp
 .DS_Store
-.ruby-version
-iterate.dat
-/spec/dump_dbl.t
-/spec/dump_int.t
-/spec/dump_mult_dbl.t
-/spec/dump_zb.t
+.rspec_status
+Gemfile.lock
+dump_*

CODE_OF_CONDUCT.md

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+# Contributor Covenant Code of Conduct
+
+## Our Pledge
+
+We as members, contributors, and leaders pledge to make participation in our community a harassment-free experience for everyone, regardless of age, body size, visible or invisible disability, ethnicity, sex characteristics, gender identity and expression, level of experience, education, socio-economic status, nationality, personal appearance, race, religion, or sexual identity and orientation.
+
+We pledge to act and interact in ways that contribute to an open, welcoming, diverse, inclusive, and healthy community.
+
+## Our Standards
+
+Examples of behavior that contributes to a positive environment for our community include:
+
+* Demonstrating empathy and kindness toward other people
+* Being respectful of differing opinions, viewpoints, and experiences
+* Giving and gracefully accepting constructive feedback
+* Accepting responsibility and apologizing to those affected by our mistakes, and learning from the experience
+* Focusing on what is best not just for us as individuals, but for the overall community
+
+Examples of unacceptable behavior include:
+
+* The use of sexualized language or imagery, and sexual attention or
+  advances of any kind
+* Trolling, insulting or derogatory comments, and personal or political attacks
+* Public or private harassment
+* Publishing others' private information, such as a physical or email
+  address, without their explicit permission
+* Other conduct which could reasonably be considered inappropriate in a
+  professional setting
+
+## Enforcement Responsibilities
+
+Community leaders are responsible for clarifying and enforcing our standards of acceptable behavior and will take appropriate and fair corrective action in response to any behavior that they deem inappropriate, threatening, offensive, or harmful.
+
+Community leaders have the right and responsibility to remove, edit, or reject comments, commits, code, wiki edits, issues, and other contributions that are not aligned to this Code of Conduct, and will communicate reasons for moderation decisions when appropriate.
+
+## Scope
+
+This Code of Conduct applies within all community spaces, and also applies when an individual is officially representing the community in public spaces. Examples of representing our community include using an official e-mail address, posting via an official social media account, or acting as an appointed representative at an online or offline event.
+
+## Enforcement
+
+Instances of abusive, harassing, or otherwise unacceptable behavior may be reported to the community leaders responsible for enforcement at [email protected]. All complaints will be reviewed and investigated promptly and fairly.
+
+All community leaders are obligated to respect the privacy and security of the reporter of any incident.
+
+## Enforcement Guidelines
+
+Community leaders will follow these Community Impact Guidelines in determining the consequences for any action they deem in violation of this Code of Conduct:
+
+### 1. Correction
+
+**Community Impact**: Use of inappropriate language or other behavior deemed unprofessional or unwelcome in the community.
+
+**Consequence**: A private, written warning from community leaders, providing clarity around the nature of the violation and an explanation of why the behavior was inappropriate. A public apology may be requested.
+
+### 2. Warning
+
+**Community Impact**: A violation through a single incident or series of actions.
+
+**Consequence**: A warning with consequences for continued behavior. No interaction with the people involved, including unsolicited interaction with those enforcing the Code of Conduct, for a specified period of time. This includes avoiding interactions in community spaces as well as external channels like social media. Violating these terms may lead to a temporary or permanent ban.
+
+### 3. Temporary Ban
+
+**Community Impact**: A serious violation of community standards, including sustained inappropriate behavior.
+
+**Consequence**: A temporary ban from any sort of interaction or public communication with the community for a specified period of time. No public or private interaction with the people involved, including unsolicited interaction with those enforcing the Code of Conduct, is allowed during this period. Violating these terms may lead to a permanent ban.
+
+### 4. Permanent Ban
+
+**Community Impact**: Demonstrating a pattern of violation of community standards, including sustained inappropriate behavior,  harassment of an individual, or aggression toward or disparagement of classes of individuals.
+
+**Consequence**: A permanent ban from any sort of public interaction within the community.
+
+## Attribution
+
+This Code of Conduct is adapted from the [Contributor Covenant][homepage], version 2.0,
+available at https://www.contributor-covenant.org/version/2/0/code_of_conduct.html.
+
+Community Impact Guidelines were inspired by [Mozilla's code of conduct enforcement ladder](https://github.com/mozilla/diversity).
+
+[homepage]: https://www.contributor-covenant.org
+
+For answers to common questions about this code of conduct, see the FAQ at
+https://www.contributor-covenant.org/faq. Translations are available at https://www.contributor-covenant.org/translations.

LICENSE.txt

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+Copyright (c) 2022 Atsushi Tatsuma
+All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are met:
+
+* Redistributions of source code must retain the above copyright notice, this
+  list of conditions and the following disclaimer.
+
+* Redistributions in binary form must reproduce the above copyright notice,
+  this list of conditions and the following disclaimer in the documentation
+  and/or other materials provided with the distribution.
+
+* Neither the name of the copyright holder nor the names of its
+  contributors may be used to endorse or promote products derived from
+  this software without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

README.md

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+# Rumale
+
+![Rumale](https://dl.dropboxusercontent.com/s/joxruk2720ur66o/rumale_header_400.png)
+
+[![Gem Version](https://badge.fury.io/rb/rumale.svg)](https://badge.fury.io/rb/rumale)
+[![BSD 3-Clause License](https://img.shields.io/badge/License-BSD%203--Clause-orange.svg)](https://github.com/yoshoku/rumale/blob/main/LICENSE.txt)
+[![Documentation](https://img.shields.io/badge/api-reference-blue.svg)](https://yoshoku.github.io/rumale/doc/)
+
+Rumale (**Ru**by **ma**chine **le**arning) 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.
+
+## Installation
+
+Add this line to your application's Gemfile:
+
+```ruby
+gem 'rumale'
+```
+
+And then execute:
+
+    $ bundle
+
+Or install it yourself as:
+
+    $ gem install rumale
+
+## Documentation
+
+- [Rumale API Documentation](https://yoshoku.github.io/rumale/doc/)
+
+## Usage
+
+### Example 1. Pendigits dataset classification
+
+Rumale provides function loading libsvm format dataset file.
+We start by downloading the pendigits dataset from LIBSVM Data web site.
+
+```bash
+$ wget https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/multiclass/pendigits
+$ wget https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/multiclass/pendigits.t
+```
+
+Training of the classifier with Linear SVM and RBF kernel feature map is the following code.
+
+```ruby
+require 'rumale'
+
+# Load the training dataset.
+samples, labels = Rumale::Dataset.load_libsvm_file('pendigits')
+
+# Map training data to RBF kernel feature space.
+transformer = Rumale::KernelApproximation::RBF.new(gamma: 0.0001, n_components: 1024, random_seed: 1)
+transformed = transformer.fit_transform(samples)
+
+# Train linear SVM classifier.
+classifier = Rumale::LinearModel::SVC.new(reg_param: 0.0001, random_seed: 1)
+classifier.fit(transformed, labels)
+
+# Save the model.
+File.open('transformer.dat', 'wb') { |f| f.write(Marshal.dump(transformer)) }
+File.open('classifier.dat', 'wb') { |f| f.write(Marshal.dump(classifier)) }
+```
+
+Classifying testing data with the trained classifier is the following code.
+
+```ruby
+require 'rumale'
+
+# Load the testing dataset.
+samples, labels = Rumale::Dataset.load_libsvm_file('pendigits.t')
+
+# Load the model.
+transformer = Marshal.load(File.binread('transformer.dat'))
+classifier = Marshal.load(File.binread('classifier.dat'))
+
+# Map testing data to RBF kernel feature space.
+transformed = transformer.transform(samples)
+
+# Classify the testing data and evaluate prediction results.
+puts("Accuracy: %.1f%%" % (100.0 * classifier.score(transformed, labels)))
+
+# Other evaluating approach
+# results = classifier.predict(transformed)
+# evaluator = Rumale::EvaluationMeasure::Accuracy.new
+# puts("Accuracy: %.1f%%" % (100.0 * evaluator.score(results, labels)))
+```
+
+Execution of the above scripts result in the following.
+
+```bash
+$ ruby train.rb
+$ ruby test.rb
+Accuracy: 98.7%
+```
+
+### Example 2. Cross-validation
+
+```ruby
+require 'rumale'
+
+# Load dataset.
+samples, labels = Rumale::Dataset.load_libsvm_file('pendigits')
+
+# Define the estimator to be evaluated.
+lr = Rumale::LinearModel::LogisticRegression.new
+
+# Define the evaluation measure, splitting strategy, and cross validation.
+ev = Rumale::EvaluationMeasure::Accuracy.new
+kf = Rumale::ModelSelection::StratifiedKFold.new(n_splits: 5, shuffle: true, random_seed: 1)
+cv = Rumale::ModelSelection::CrossValidation.new(estimator: lr, splitter: kf, evaluator: ev)
+
+# Perform 5-cross validation.
+report = cv.perform(samples, labels)
+
+# Output result.
+mean_accuracy = report[:test_score].sum / kf.n_splits
+puts "5-CV mean accuracy: %.1f%%" % (100.0 * mean_accuracy)
+```
+
+Execution of the above scripts result in the following.
+
+```bash
+$ ruby cross_validation.rb
+5-CV mean accuracy: 95.4%
+```
+
+
+## Speedup
+
+### Numo::Linalg
+Rumale uses [Numo::NArray](https://github.com/ruby-numo/numo-narray) for typed arrays.
+Loading the [Numo::Linalg](https://github.com/ruby-numo/numo-linalg) allows to perform matrix and vector product of Numo::NArray
+using BLAS libraries.
+Some machine learning algorithms frequently compute matrix and vector products,
+the execution speed of such algorithms can be expected to be accelerated.
+
+Install Numo::Linalg gem.
+
+```bash
+$ gem install numo-linalg
+```
+
+In ruby script, just load Numo::Linalg along with Rumale.
+
+```ruby
+require 'numo/linalg/autoloader'
+require 'rumale'
+```
+
+### Numo::OpenBLAS
+[Numo::OpenBLAS](https://github.com/yoshoku/numo-openblas) downloads and builds OpenBLAS during installation
+and uses that as a background library for Numo::Linalg.
+
+Install compilers for building OpenBLAS.
+
+```bash
+$ sudo apt-get install gcc gfortran make
+```
+
+Install Numo::OpenBLAS gem.
+
+```bash
+$ gem install numo-openblas
+```
+
+Load Numo::OpenBLAS gem instead of Numo::Linalg.
+
+```ruby
+require 'numo/openblas'
+require 'rumale'
+```
+
+### Numo::BLIS
+[Numo::BLIS](https://github.com/yoshoku/numo-blis) downloads and builds BLIS during installation
+and uses that as a background library for Numo::Linalg.
+BLIS is one of the high-performance BLAS as with OpenBLAS,
+and using that can be expected to speed up of processing in Rumale.
+
+Install Numo::BLIS gem.
+
+```bash
+$ gem install numo-blis
+```
+
+Load Numo::BLIS gem instead of Numo::Linalg.
+
+```ruby
+require 'numo/blis'
+require 'rumale'
+```
+
+### Parallel
+Several estimators in Rumale support parallel processing.
+Parallel processing in Rumale is realized by [Parallel](https://github.com/grosser/parallel) gem,
+so install and load it.
+
+```bash
+$ gem install parallel
+```
+
+```ruby
+require 'parallel'
+require 'rumale'
+```
+
+Estimators that support parallel processing have n_jobs parameter.
+When -1 is given to n_jobs parameter, all processors are used.
+
+```ruby
+estimator = Rumale::Ensemble::RandomForestClassifier.new(n_jobs: -1, random_seed: 1)
+```
+
+## Related Projects
+
+- [Rumale::SVM](https://github.com/yoshoku/rumale-svm) provides support vector machine algorithms in LIBSVM and LIBLINEAR with Rumale interface.
+- [Rumale::Torch](https://github.com/yoshoku/rumale-torch) provides the learning and inference by the neural network defined in torch.rb with Rumale interface.
+
+## License
+
+The gem is available as open source under the terms of the [BSD-3-Clause License](https://opensource.org/licenses/BSD-3-Clause).