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| <!doctype html> | ||
| <html lang="en" data-bs-theme="light"> | ||
| <head> | ||
| <meta charset="utf-8"> | ||
| <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"> | ||
| <meta name="description" content="User's manual for RFFLearn, a library for random Fourier feature based ML models"> | ||
| <meta name="keywords" content="random Fourier features,rff,fast machine learning,Tetsuya Ishikawa"> | ||
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| <meta name="author" content="Tetsuya Ishikawa, tiskw111@gmail.com"> | ||
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| <title>RFFLearn: User's Manual - API Reference</title> | ||
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| <!-- Header --> | ||
| <header> | ||
| <div class="container mx-auto"><div class="row"> | ||
| <p class="text-center"><img src="./images/logo_long.svg" style="width:640px;" alt="rfflearn_logo"></p> | ||
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| <main> | ||
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| <!-- --> | ||
| <section class="container py-3"> | ||
| <h1 class="py-2 border-bottom" id="setting_up">API Reference</h1> | ||
| <p>The RFFLearn library consists of the several sub modules. <!-- | ||
| -->Click the module name to see the details of each module.</p> | ||
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| <div class="row align-items-center justify-content-center"><div class="col-8"><table class="table table-hover"> | ||
| <thead><tr> | ||
| <th scope="col">Sub module name</th> | ||
| <th scope="col">Description</th> | ||
| </tr></thead> | ||
| <tbody><tr> | ||
| <td><a href="#rfflearn_cpu">rfflearn.cpu</a></td> | ||
| <td>Regressors and classifiers of random Fourier features on CPU.</td> | ||
| </tr><tr> | ||
| <td><a href="#rfflearn_gpu">rfflearn.gpu</a></td> | ||
| <td>Regressors and classifiers of random Fourier features on GPU.</td> | ||
| </tr><tr> | ||
| <td><a href="#rfflearn_explainer">rfflearn.explainer</a></td> | ||
| <td>Classes and functions to get model explanation for RFF-based models.</td> | ||
| </tr><tr> | ||
| <td><a href="#rfflearn_tuner">rfflearn.tuner</a></td> | ||
| <td>Classes and functions for automatic hyperparameter tuning.</td> | ||
| </tr></tbody> | ||
| </table></div></div> | ||
| </section> | ||
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| <section class="container py-3"> | ||
| <h2 class="py-2" id="rfflearn_cpu">rfflearn.cpu</h2> | ||
| <p>Sub module for machine learning algorithm of random Fourier feature runnable on CPU. <!-- | ||
| -->This sub module contains machine learning algorithm (e.g. regressors, classifiers) which is designed to be run on CPU. <!-- | ||
| -->Interfaces of classes and functions in this module have quite close interfaces with scikit-learn library. <!-- | ||
| -->Most (but not all) of the classes uses scikit-learn as a back end.</p> | ||
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| <div class="row align-items-center justify-content-center"><div class="col-8"><table class="table table-hover"> | ||
| <thead><tr> | ||
| <th scope="col">Class name</th> | ||
| <th scope="col">Description</th> | ||
| </tr></thead> | ||
| <tbody><tr> | ||
| <td><a href="./api_reference_RFFCCA.html">rfflearn.cpu.RFFCCA</a></td> | ||
| <td>Canonical correlation analysis with random Fourier features.</td> | ||
| </tr><tr> | ||
| <td><a href="./api_reference_RFFGPC.html">rfflearn.cpu.RFFGPC</a></td> | ||
| <td>Gaussian process classification with random Fourier features.</td> | ||
| </tr><tr> | ||
| <td><a href="./api_reference_RFFGPR.html">rfflearn.cpu.RFFGPR</a></td> | ||
| <td>Gaussian process regression with random Fourier features.</td> | ||
| </tr><tr> | ||
| <td><a href="./api_reference_RFFPCA.html">rfflearn.cpu.RFFPCA</a></td> | ||
| <td>Principal component analysis with random Fourier features.</td> | ||
| </tr><tr> | ||
| <td><a href="./api_reference_RFFRegression.html">rfflearn.cpu.RFFRegression</a></td> | ||
| <td>Regression with random Fourier features.</td> | ||
| </tr><tr> | ||
| <td><a href="./api_reference_RFFSVC.html">rfflearn.cpu.RFFSVC</a></td> | ||
| <td>Support vector classification with random Fourier features.</td> | ||
| </tr><tr> | ||
| <td><a href="./api_reference_RFFSVR.html">rfflearn.cpu.RFFSVR</a></td> | ||
| <td>Support vector regression with random Fourier features.</td> | ||
| </tr><tr> | ||
| <td><a href="./api_reference_RFFBatchSVC.html">rfflearn.cpu.RFFBatchSVC</a></td> | ||
| <td>Batch learning version of <code>rfflearn.cpu.RFFSVC</code>.</td> | ||
| </tr><tr> | ||
| <td><a href="#">rfflearn.cpu.ORF*</a></td> | ||
| <td>ORF (orthogonal random features) version of estimators. For example, <code>rfflearn.cpu.ORFSVC</code> <!-- | ||
| -->is a support vector classifier with ORF. The arguments of constructor and member functions are the same as RFF version, <!-- | ||
| -->so please see the document of <code>rfflearn.cpu.RFF*</code> for the details of the usage of each class.</td> | ||
| </tr><tr> | ||
| <td><a href="#">rfflearn.cpu.QRF*</a></td> | ||
| <td>QRF (quasi random features) version of estimators. For example, <code>rfflearn.cpu.QRFSVC</code> <!-- | ||
| -->is a support vector classifier with QRF. The arguments of constructor and member functions are the same as RFF version, <!-- | ||
| -->so please see the document of <code>rfflearn.cpu.RFF*</code> for the details of the usage of each class.</td> | ||
| </tr></tbody> | ||
| </table></div></div> | ||
| </section> | ||
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| <section class="container py-3"> | ||
| <h2 class="py-2" id="rfflearn_gpu">rfflearn.gpu</h2> | ||
| <p>Sub module for regressors and classifiers of random Fourier feature runnable on GPU. <!-- | ||
| -->This module is designed to have the same interface as <code>rfflearn.cpu</code>. <!-- | ||
| -->See the <a href="#rfflearn_cpu">API reference of rfflearn.cpu</a> for the details of this module.</p> | ||
| </section> | ||
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| <section class="container py-3"> | ||
| <h2 class="py-2" id="rfflearn_explainer">rfflearn.explainer</h2> | ||
| <p>TBD</p> | ||
| </section> | ||
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| <section class="container py-3"> | ||
| <h2 class="py-2" id="rfflearn_tuner">rfflearn.tuner</h2> | ||
| <p>TBD</p> | ||
| </section> | ||
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| </main> | ||
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| <p>Copyright (C) 2017-<span id="thisYear"></span> Tetsuya Ishikawa</p> | ||
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