(1) 簡介：
(2) 算法描述：
(3)
1 <?php
2 /*
3 *Naive Bayes樸素貝葉斯算法（分類算法的實現）
4 */
5
6 /*
7 *把.txt中的內容讀到數組中保存
8 *$filename:文件名稱
9 */
10 //--------------------------------------------------------------------
11 function getFileContent($filename)
12 {
13 $array = array(null);
14 $content = file_get_contents($filename);
15 $result = explode("\r\n",$content);
16 //print_r(count($result));
17 for($j=0;$j<count($result);$j++)
18 {
19 //print_r($result[$j]."<br>");
20 $con = explode(" ",$result[$j]);
21 array_push($array,$con);
22 }
23 array_splice($array,0,1);
24 return $array;
25 }
26 //--------------------------------------------------------------------
27
28
29 /*
30 *NaiveBayes樸素貝葉斯算法
31 *$test:測試文本；$train：訓練文本；$flagsyes：yes；$flagsno：no
32 */
33 //--------------------------------------------------------------------
34 function NaiveBayes($test,$train,$flagsyes,$flagsno)
35 {
36 $count_yes = 0;
37 $num = count($train[0]);
38 for($i=1;$i<count($train);$i++)
39 {
40 if($train[$i][$num-1]==$flagsyes)$count_yes++;
41 }
42 $p_yes = $count_yes / (count($train)-1);
43 $p_no = 1- $p_yes;
44
45 $count_no = count($train)-1 - $count_yes;
46
47
48 for($i=1;$i<count($test)-1;$i++)
49 {
50 $testnumyes = 0;
51 $testnumno = 0;
52 for($j=1;$j<count($train);$j++)
53 {
54 if(($train[$j][$i]==$test[$i])&&($train[$j][count($test)-1]==$flagsyes))$testnumyes++;
55 else if(($train[$j][$i]==$test[$i])&&($train[$j][count($test)-1]==$flagsno))$testnumno++;
56 }
57
58 $array_yes[$i] = $testnumyes / $count_yes ;
59 $array_no[$i] = $testnumno / $count_no ;
60 /*
61 print_r($testnumyes."<br>");
62 print_r($testnumno."<br>");
63 print_r($count_yes."<br>");
64 print_r($count_no."<br>");
65 print_r($array_no[$i]."<br>");
66 */
67 }
68
69 $py=1;
70 $pn=1;
71 for($i=1;$i<count($test)-1;$i++){
72 $py *= $array_yes[$i];
73 $pn *= $array_no[$i];
74 }
75
76 $py *= $p_yes;
77 $pn *= $p_no;
78
79 if($py>$pn)return $flagsyes;
80 else return $flagsno;
81
82 /* print_r($py."<br>");
83 print_r($pn."<br>");
84 */
85
86 }
87 //--------------------------------------------------------------------
88
89 $train = getFileContent("train.txt");
90 $test = getFileContent("test.txt");
91
92 for($i=1;$i<count($test);$i++)
93 {
94 $test[$i][count($test[0])-1] = NaiveBayes($test[$i],$train,Y,N);
95 }
96
97 /*
98 *將數組中的內容讀到.txt中
99 */
100 //--------------------------------------------------------------------
101 $fp= fopen('result.txt','wb');
102 for($i=0;$i<count($test);$i++)
103 {
104 $temp = NULL;
105 for($j=0;$j<count($test[$i]);$j++)
106 {
107 $temp = $test[$i][$j]."\t";
108 fwrite($fp,$temp);
109 }
110 fwrite($fp,"\r\n");
111 }
112 fclose($fp);
113 //--------------------------------------------------------------------
114
115 /*
116 *打印輸出
117 */
118 //--------------------------------------------------------------------
119 echo "<pre>";
120 print_r($test);
121 echo "</pre>";
122 //--------------------------------------------------------------------
123 ?>
