/**
* Train ANN incrementally
* @param array input vector
* @param array output vector
* @return bool true on success, false on error
*/
public function train(array $input_vector, array $output_vector)
{
$this->checkIfAnnIsAssigned();
return fann_train($this->annId, $input_vector, $output_vector);
}
* long fann_get_total_connections(resource ann)
*
* If you have any questions or comments, please e-mail Evan Nemerson
* <*****@*****.**>
*/
/* If you don't want to compile FANN into PHP... */
if (!extension_loaded('fann')) {
if (!dl('fann.so')) {
exit("You must install the FANN extension. You can get it from http://fann.sf.net/\n");
}
}
/* Create an artificial neural network */
$ann = fann_create(array(2, 4, 1), 1.0, 0.7);
/* To load from a file, you can use. If your version of PHP includes the streams API (4.3.0+ ?),
* this can be anything accessible through streams (http, ftp, https, etc) */
// $ann = fann_create("http://example.com/xor_float.net");
/* Train the network using the same data as is in the xor.data file */
fann_train($ann, array(array(array(0, 0), array(0)), array(array(0, 1), array(1)), array(array(1, 0), array(1)), array(array(1, 1), array(0))), 100000, 1.0E-5, 1000);
/* To achieve the same effect as the above with the data stored in an external file... Also works
* with the streams API, when available. */
// fann_train($ann, '/home/tadpole/local/src/fann/examples/xor.data', 100000, 0.00001, 1000);
print_r(fann_run($ann, array(0, 0)));
// Should be ~ 0
print_r(fann_run($ann, array(0, 1)));
// Should be ~ 1
print_r(fann_run($ann, array(1, 0)));
// Should be ~ 1
print_r(fann_run($ann, array(1, 1)));
// Should be ~ 0
/* This function is pretty simple. It will use the streams API if available. */
fann_save($ann, 'xor_float.net');
