libsvm的C++使用

看了不少博客，卻想不明白怎麼把libsvm的C++跑起來。

但是一旦跑起來了，就覺得自己蠢的像馬。

1.新建一個VS2010工程，把svm.h和svm.cpp拉進來

2.考慮自己訓練一個model

2.1 把svm-train.c拉進來

    svm-train.c裏給了main函數，具體如下：

    需要給出的是：訓練數據的文件；保存模型的名字，隨便命名就好啦。

int main(int argc, char **argv)                                  //main in train.c
{
	char input_file_name[1024]; // a file with training data
	char model_file_name[1024]; // just a name of saving model
	const char *error_msg;

	parse_command_line(argc, argv, input_file_name, model_file_name); // command line is configured in the properties of project
	read_problem(input_file_name);                                    // just check
	error_msg = svm_check_parameter(&prob,¶m);


	if(error_msg)
	{
		fprintf(stderr,"ERROR: %s\n",error_msg);
		exit(1);
	}

	if(cross_validation)
	{
		do_cross_validation();
	}
	else
	{
		model = svm_train(&prob,¶m);
		if(svm_save_model(model_file_name,model))
		{
			fprintf(stderr, "can't save model to file %s\n", model_file_name);
			exit(1);
		}
		svm_free_and_destroy_model(&model);
	}
	svm_destroy_param(¶m);
	free(prob.y);
	free(prob.x);
	free(x_space);
	free(line);

	return 0;
}

2.1 造數據集

數據集的格式要符合

label 1:feature1 2:feature2 3:feature3 \n

也就是先給label，空格，然後是index冒號特徵1空格index冒號特徵2...sample與sample之間換行。

README裏就是這麼說的，沒辦法哦，如果不想用這樣的格式，那就自己倒騰唄。

我的數據如下圖：

2.3 配置訓練參數

具體的參數配置代碼裏給了；-s -t啥的也可以不配，有默認值；

下面是我的配置參數，在工程的屬性裏配置的。

-s 0 -t 0 -h 0 CU16_QP22_Valid_labels_libSVM_less.data myModel

void exit_with_help()
{
	printf(
	"Usage: svm-train [options] training_set_file [model_file]\n"
	"options:\n"
	"-s svm_type : set type of SVM (default 0)\n"
	"	0 -- C-SVC		(multi-class classification)\n"
	"	1 -- nu-SVC		(multi-class classification)\n"
	"	2 -- one-class SVM\n"
	"	3 -- epsilon-SVR	(regression)\n"
	"	4 -- nu-SVR		(regression)\n"
	"-t kernel_type : set type of kernel function (default 2)\n"
	"	0 -- linear: u'*v\n"
	"	1 -- polynomial: (gamma*u'*v + coef0)^degree\n"
	"	2 -- radial basis function: exp(-gamma*|u-v|^2)\n"
	"	3 -- sigmoid: tanh(gamma*u'*v + coef0)\n"
	"	4 -- precomputed kernel (kernel values in training_set_file)\n"
	"-d degree : set degree in kernel function (default 3)\n"
	"-g gamma : set gamma in kernel function (default 1/num_features)\n"
	"-r coef0 : set coef0 in kernel function (default 0)\n"
	"-c cost : set the parameter C of C-SVC, epsilon-SVR, and nu-SVR (default 1)\n"
	"-n nu : set the parameter nu of nu-SVC, one-class SVM, and nu-SVR (default 0.5)\n"
	"-p epsilon : set the epsilon in loss function of epsilon-SVR (default 0.1)\n"
	"-m cachesize : set cache memory size in MB (default 100)\n"
	"-e epsilon : set tolerance of termination criterion (default 0.001)\n"
	"-h shrinking : whether to use the shrinking heuristics, 0 or 1 (default 1)\n"
	"-b probability_estimates : whether to train a SVC or SVR model for probability estimates, 0 or 1 (default 0)\n"
	"-wi weight : set the parameter C of class i to weight*C, for C-SVC (default 1)\n"
	"-v n: n-fold cross validation mode\n"
	"-q : quiet mode (no outputs)\n"
	);
	exit(1);
}

2.4 訓練結果

感覺要訓好久，但是可以看到結果了呀，訓完之後屏幕輸出就是這樣。。。

3. 測試（predict）

把svm-predict拉進工程，svm-train.c移出去

配置使用的是：

-b 0  CU16_QP22_Test_labels_libSVM.data myModel predFile.txt

具體的參數可以參考：

void exit_with_help()
{
	printf(
	"Usage: svm-predict [options] test_file model_file output_file\n"
	"options:\n"
	"-b probability_estimates: whether to predict probability estimates, 0 or 1 (default 0); for one-class SVM only 0 is supported\n"
	"-q : quiet mode (no outputs)\n"
	);
	exit(1);
}