PHP机器学习库php-ml的简单测试和使用

 1 php
 2 include_once ‘./src/jpgraph.php‘;
 3 include_once ‘./src/jpgraph_line.php‘;
 4 
 5 $g = new Graph(1920,1080);//jpgraph的绘制操作
 6 $g->SetScale("textint");
 7 $g->title->Set(‘data‘);
 8 
 9 //文件的处理
10 $file = fopen(‘data.txt‘,‘r‘);
11 $labels = array();
12 while(!feof($file)){
13     $data = explode(‘    ‘,fgets($file));        
14     $data[1] = str_replace(‘,‘,‘.‘,$data[1]);//数据处理，将数据中的逗号修正为小数点
15     $labels[(int)$data[0]] = (float)$data[1];//这里将数据以键值的方式存入数组，方便我们根据键来排序
16 }  
17 
18 ksort($labels);//按键的大小排序
19 
20 $x = array();//x轴的表示数据
21 $y = array();//y轴的表示数据
22 foreach($labels as $key=>$value){
23     array_push($x,$key);
24     array_push($y,$value);
25 }
26 
27 
28 $linePlot = new LinePlot($y);
29 $g->xaxis->SetTickLabels($x);  
30 $linePlot->SetLegend(‘data‘);
31 $g->Add($linePlot);
32 $g->Stroke();

 1 php
 2     require ‘vendor/autoload.php‘;
 3 
 4     use Phpml\Regression\LeastSquares;
 5     use Phpml\ModelManager;
 6 
 7     $file = fopen(‘data.txt‘,‘r‘);
 8     $samples = array();
 9     $labels = array();
10     $i = 0;
11     while(!feof($file)){
12         $data = explode(‘    ‘,fgets($file));
13         $samples[$i][0] = (int)$data[0];
14         $data[1] = str_replace(‘,‘,‘.‘,$data[1]);
15         $labels[$i] = (float)$data[1];
16         $i ++;
17     }   
18     fclose($file);
19 
20     $regression = new LeastSquares();
21     $regression->train($samples,$labels);
22 
23     //这个a数组是根据我们对原数据处理后的x值给出的，做测试用。
24     $a = [0,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,20,22,23,24,25,26,27,29,30,31,37,40,41,45,48,53,55,57,60,61,108,124];
25     for($i = 0; $i count($a); $i ++){
26         file_put_contents("putput.txt",($regression->predict([$a[$i]]))."\n",FILE_APPEND); //以追加的方式存入文件       
27     }

 1 php
 2 include_once ‘./src/jpgraph.php‘;
 3 include_once ‘./src/jpgraph_line.php‘;
 4 
 5 $g = new Graph(1920,1080);
 6 $g->SetScale("textint");
 7 $g->title->Set(‘data‘);
 8 
 9 $file = fopen(‘putput.txt‘,‘r‘);
10 $y = array();
11 $i = 0;
12 while(!feof($file)){
13     $y[$i] = (float)(fgets($file));
14     $i ++;            
15 }  
16 
17 $x = [0,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,20,22,23,24,25,26,27,29,30,31,37,40,41,45,48,53,55,57,60,61,108,124];
18 
19 $linePlot = new LinePlot($y);
20 $g->xaxis->SetTickLabels($x);  
21 $linePlot->SetLegend(‘data‘);
22 $g->Add($linePlot);
23 $g->Stroke();

 1 php
 2 require ‘vendor/autoload.php‘;
 3 
 4 use Phpml\Classification\SVC;
 5 use Phpml\SupportVectorMachine\Kernel;
 6 use Phpml\Dataset\CsvDataset;
 7 
 8 $dataset = new CsvDataset(‘Iris.csv‘ , 4, false);
 9 $classifier = new SVC(Kernel::LINEAR,$cost = 1000);
10 $classifier->train($dataset->getSamples(),$dataset->getTargets());
11 
12 echo $classifier->predict([$argv[1],$argv[2],$argv[3],$argv[4]]);//$argv是命令行参数，调试这种程序使用命令行较方便