superml/index.html at master · RcppDeepState/superml · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
<!DOCTYPE html>
<!-- Generated by pkgdown: do not edit by hand --><html lang="en">
<head>
<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
<meta charset="utf-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Build Machine Learning Models Like Using Python's Scikit-Learn Library in R • SuperML</title>
<!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script><!-- Bootstrap --><link href="https://cdnjs.cloudflare.com/ajax/libs/bootswatch/3.4.0/flatly/bootstrap.min.css" rel="stylesheet" crossorigin="anonymous">
<script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script><!-- bootstrap-toc --><link rel="stylesheet" href="bootstrap-toc.css">
<script src="bootstrap-toc.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous">
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous">
<!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="pkgdown.css" rel="stylesheet">
<script src="pkgdown.js"></script><meta property="og:title" content="Build Machine Learning Models Like Using Python's Scikit-Learn Library in R">
<meta property="og:description" content="The idea is to provide a standard interface
             to users who use both R and Python for building machine learning models.
             This package provides a scikit-learn's fit, predict interface to
             train machine learning models in R.    ">
<!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
<![endif]-->
</head>
<body data-spy="scroll" data-target="#toc">


    <div class="container template-home">
      <header><div class="navbar navbar-default navbar-fixed-top" role="navigation">
  <div class="container">
    <div class="navbar-header">
      <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false">
        <span class="sr-only">Toggle navigation</span>
        <span class="icon-bar"></span>
        <span class="icon-bar"></span>
        <span class="icon-bar"></span>
      </button>
      <span class="navbar-brand">
        <a class="navbar-link" href="index.html">SuperML</a>
        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.5.5</span>
      </span>
    </div>

    <div id="navbar" class="navbar-collapse collapse">
      <ul class="nav navbar-nav">
<li>
  <a href="index.html">
    <span class="fa fa-home fa-lg"></span>

  </a>
</li>
<li class="dropdown">
  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false">
    Tutorials

    <span class="caret"></span>
  </a>
  <ul class="dropdown-menu" role="menu">
<li>
      <a href="articles/superml_tutorial.html">Introduction to superml</a>
    </li>
    <li>
      <a href="articles/Guide-to-CountVectorizer.html">Guide to CountVectorizer</a>
    </li>
    <li>
      <a href="articles/Guide-to-TfidfVectorizer.html">Guide to TfIdfVectorizer</a>
    </li>
  </ul>
</li>
<li>
  <a href="reference/index.html">Reference</a>
</li>
<li>
  <a href="news/index.html">News</a>
</li>
      </ul>
<ul class="nav navbar-nav navbar-right">
<li>
  <a href="https://github.com/saraswatmks/superml" class="external-link">
    <span class="fa fa-github fa-lg"></span>

  </a>
</li>
<li>
  <a href="https://www.linkedin.com/in/saraswatmanish/" class="external-link">
    <span class="fa fa-linkedin fa-lg"></span>

  </a>
</li>
      </ul>
</div>
<!--/.nav-collapse -->
  </div>
<!--/.container -->
</div>
<!--/.navbar -->


      </header><div class="row">
  <div class="contents col-md-9">


<div class="section level1">
<div class="page-header"><h1 id="superml">SuperML<a class="anchor" aria-label="anchor" href="#superml"></a>
</h1></div>
<p>The goal of SuperML is to provide sckit-learn’s <code>fit</code>,<code>predict</code>,<code>transform</code> standard way of building machine learning models in R. It is build on top of latest r-packages which provides optimized way of training machine learning models.</p>
<div class="section level2">
<h2 id="installation">Installation<a class="anchor" aria-label="anchor" href="#installation"></a>
</h2>
<p>You can install latest stable cran version using (recommended):</p>
<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/utils/install.packages.html" class="external-link">install.packages</a></span><span class="op">(</span><span class="st">"superml"</span><span class="op">)</span>
<span class="fu"><a href="https://rdrr.io/r/utils/install.packages.html" class="external-link">install.packages</a></span><span class="op">(</span><span class="st">"superml"</span>, dependencies<span class="op">=</span><span class="cn">TRUE</span><span class="op">)</span> <span class="co"># to install all dependencies at once</span></code></pre></div>
<p>You can install superml from github with:</p>
<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="co"># install.packages("devtools")</span>
<span class="fu">devtools</span><span class="fu">::</span><span class="fu">install_github</span><span class="op">(</span><span class="st">"saraswatmks/superml"</span><span class="op">)</span></code></pre></div>
</div>
<div class="section level2">
<h2 id="description">Description<a class="anchor" aria-label="anchor" href="#description"></a>
</h2>
<p>In superml, every machine learning algorithm is called as a <code>trainer</code>. Following is the list of trainers available as of today:<br></p>
<ul>
<li>LMTrainer: used to train linear, logistic, ridge, lasso models</li>
<li>KNNTrainer: K-Nearest Neighbour Models</li>
<li>KMeansTrainer: KMeans Model</li>
<li>NBTrainer: Naive Baiyes Model</li>
<li>SVMTrainer: SVM Model</li>
<li>RFTrainer: Random Forest Model</li>
<li>XGBTrainer: XGBoost Model</li>
</ul>
<p>In addition, there are other useful functions to support modeling tasks such as:</p>
<ul>
<li>CountVectorizer: Create Bag of Words model</li>
<li>TfidfVectorizer: Create TF-IDF feature model</li>
<li>LabelEncoder: Convert categorical features to numeric</li>
<li>GridSearchCV: For hyperparameter optimization</li>
<li>RandomSearchCV: For hyperparameter optimization</li>
<li>kFoldMean: Target encoding</li>
<li>smoothMean: Target encoding</li>
</ul>
<p>To compute text similarity, following functions are available:</p>
<ul>
<li>bm_25: Computes bm25 distance</li>
<li>dot: Computes dot product between two vectors</li>
<li>dotmat: Computes dot product between vector &amp; matrix</li>
</ul>
</div>
<div class="section level2">
<h2 id="usage">Usage<a class="anchor" aria-label="anchor" href="#usage"></a>
</h2>
<p>Any machine learning model can be trained using the following steps:</p>
<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/utils/data.html" class="external-link">data</a></span><span class="op">(</span><span class="va">iris</span><span class="op">)</span>
<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/saraswatmks/superml" class="external-link">superml</a></span><span class="op">)</span>

<span class="co"># random forest</span>
<span class="va">rf</span> <span class="op">&lt;-</span> <span class="va"><a href="reference/RFTrainer.html">RFTrainer</a></span><span class="op">$</span><span class="fu">new</span><span class="op">(</span>n_estimators <span class="op">=</span> <span class="fl">100</span><span class="op">)</span>
<span class="va">rf</span><span class="op">$</span><span class="fu">fit</span><span class="op">(</span><span class="va">iris</span>, <span class="st">"Species"</span><span class="op">)</span>
<span class="va">pred</span> <span class="op">&lt;-</span> <span class="va">rf</span><span class="op">$</span><span class="fu">predict</span><span class="op">(</span><span class="va">iris</span><span class="op">)</span></code></pre></div>
</div>
<div class="section level2">
<h2 id="documentation">Documentation<a class="anchor" aria-label="anchor" href="#documentation"></a>
</h2>
<p>The documentation can be found here: <a href="https://saraswatmks.github.io/superml/">SuperML Documentation</a></p>
</div>
<div class="section level2">
<h2 id="contributions--support">Contributions &amp; Support<a class="anchor" aria-label="anchor" href="#contributions--support"></a>
</h2>
<p>SuperML is my ambitious effort to help people train machine learning models in R as easily as they do in python. I encourage you to use this library, post bugs and feature suggestions in the issues above.</p>
</div>
</div>

  </div>

  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
    <div class="links">
<h2 data-toc-skip>Links</h2>
<ul class="list-unstyled">
<li><a href="https://cloud.r-project.org/package=superml" class="external-link">View on CRAN</a></li>
<li><a href="https://github.com/saraswatmks/superml/" class="external-link">Browse source code</a></li>
<li><a href="https://github.com/saraswatmks/superml/issues" class="external-link">Report a bug</a></li>
</ul>
</div>

<div class="license">
<h2 data-toc-skip>License</h2>
<ul class="list-unstyled">
<li>
<a href="https://www.r-project.org/Licenses/GPL-3" class="external-link">GPL-3</a> | file <a href="LICENSE-text.html">LICENSE</a>
</li>
</ul>
</div>


<div class="citation">
<h2 data-toc-skip>Citation</h2>
<ul class="list-unstyled">
<li><a href="authors.html#citation">Citing superml</a></li>
</ul>
</div>

<div class="developers">
<h2 data-toc-skip>Developers</h2>
<ul class="list-unstyled">
<li>Manish Saraswat <br><small class="roles"> Author, maintainer </small>  </li>
</ul>
</div>

<div class="dev-status">
<h2 data-toc-skip>Dev status</h2>
<ul class="list-unstyled">
<li><a href="https://cran.r-project.org/package=superml" class="external-link"><img src="https://www.r-pkg.org/badges/version/superml" alt="CRAN status"></a></li>
<li><a href="https://cran.r-project.org/package=superml" class="external-link"><img src="http://cranlogs.r-pkg.org/badges/superml" alt="Downloads"></a></li>
<li><a href="https://github.com/saraswatmks/superml/actions" class="external-link"><img src="https://github.com/saraswatmks/superml/workflows/R-CMD-check/badge.svg" alt="R-CMD-check"></a></li>
</ul>
</div>

  </div>
</div>


      <footer><div class="copyright">
  <p></p>
<p>Developed by Manish Saraswat.</p>
</div>

<div class="pkgdown">
  <p></p>
<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.3.</p>
</div>

      </footer>
</div>


  </body>
</html>