Examples
The basic process is to define parameters, supply training data to generate a model on, then make predictions based on the model. There are a default set of parameters that should get some results with most any input, so we'll start by looking at the data.
Data is supplied in either a file, a stream, or as an array. If supplied in a file or a stream, it must contain one line per training example, which must be formatted as an integer class (usually 1 and -1) followed by a series of feature/value pairs, in increasing feature order. The features are integers, the values floats, usually scaled 0-1. For example:
-1 1:0.43 3:0.12 9284:0.2
In a document classification problem, say a spam checker, each line would represent a document. There would be two classes, -1 for spam, 1 for ham. Each feature would represent some word, and the value would represent that importance of that word to the document (perhaps the frequency count, with the total scaled to unit length). Features that were 0 (e.g. the word did not appear in the document at all) would simply not be included.
In array mode, the data must be passed as an array of arrays. Each sub-array must have the class as the first element, then key => value sets for the feature values pairs.
This data is passed to the SVM class's train function, which will return an SVM model is successful.
Once a model has been generated, it can be used to make predictions about previously unseen data. This can be passed as an array to the model's predict function, in the same format as before, but without the label. The response will be the class.
Models can be saved and restored as required, using the save and load functions, which both take a file location.
Example #1 Train from array
<?php
$data = array(
array(-1, 1 => 0.43, 3 => 0.12, 9284 => 0.2),
array(1, 1 => 0.22, 5 => 0.01, 94 => 0.11),
);
$svm = new SVM();
$model = $svm->train($data);
$data = array(1 => 0.43, 3 => 0.12, 9284 => 0.2);
$result = $model->predict($data);
var_dump($result);
$model->save('model.svm');
?>
The above example will output something similar to:
int(-1)
Example #2 Train from a file
<?php
$svm = new SVM();
$model = $svm->train("traindata.txt");
?>
English translation
You have asked to visit this site in English. For now, only the interface is translated, but not all the content yet.If you want to help me in translations, your contribution is welcome. All you need to do is register on the site, and send me a message asking me to add you to the group of translators, which will give you the opportunity to translate the pages you want. A link at the bottom of each translated page indicates that you are the translator, and has a link to your profile.
Thank you in advance.
Document created the 30/01/2003, last modified the 26/10/2018
Source of the printed document:https://www.gaudry.be/en/php-rf-svm.examples.html
The infobrol is a personal site whose content is my sole responsibility. The text is available under CreativeCommons license (BY-NC-SA). More info on the terms of use and the author.
References
These references and links indicate documents consulted during the writing of this page, or which may provide additional information, but the authors of these sources can not be held responsible for the content of this page.
The author This site is solely responsible for the way in which the various concepts, and the freedoms that are taken with the reference works, are presented here. Remember that you must cross multiple source information to reduce the risk of errors.