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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,29 @@ | ||
| #pragma once | ||
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| #include <svm.h> | ||
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| // userdata NSSvmTrain(players origin) | ||
| SQRESULT NSSvmTrain(HSquirrelVM* sqvm) | ||
| { | ||
| //g_pSquirrel<ScriptContext::SERVER>->__sq_get | ||
| return SQRESULT_NOTNULL; | ||
| } | ||
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| // integer NSSvmPredict(point origin) | ||
| SQRESULT NSSvmPredict(HSquirrelVM* sqvm) | ||
| { | ||
| Vector3 vec = g_pSquirrel<ScriptContext::CLIENT>->getvector(sqvm,-1); | ||
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| // code | ||
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| g_pSquirrel<ScriptContext::SERVER>->pushinteger(sqvm,1); | ||
| return SQRESULT_NOTNULL; | ||
| } | ||
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| ON_DLL_LOAD_CLIENT_RELIESON("client.dll", ScriptPlayerInfo, ClientSquirrel, (CModule module)) | ||
| { | ||
| g_pSquirrel<ScriptContext::SERVER>->AddFuncRegistration("userdata", "NSSvmTrain", "", "", NSSvmTrain); | ||
| g_pSquirrel<ScriptContext::SERVER>->AddFuncRegistration("int", "NSSvmPredict", "vector origin", "", NSSvmPredict); | ||
| } |
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,104 @@ | ||
| #ifndef _LIBSVM_H | ||
| #define _LIBSVM_H | ||
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| #define LIBSVM_VERSION 325 | ||
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| #ifdef __cplusplus | ||
| extern "C" { | ||
| #endif | ||
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| extern int libsvm_version; | ||
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| struct svm_node | ||
| { | ||
| int index; | ||
| double value; | ||
| }; | ||
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| struct svm_problem | ||
| { | ||
| int l; | ||
| double *y; | ||
| struct svm_node **x; | ||
| }; | ||
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| enum { C_SVC, NU_SVC, ONE_CLASS, EPSILON_SVR, NU_SVR }; /* svm_type */ | ||
| enum { LINEAR, POLY, RBF, SIGMOID, PRECOMPUTED }; /* kernel_type */ | ||
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| struct svm_parameter | ||
| { | ||
| int svm_type; | ||
| int kernel_type; | ||
| int degree; /* for poly */ | ||
| double gamma; /* for poly/rbf/sigmoid */ | ||
| double coef0; /* for poly/sigmoid */ | ||
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| /* these are for training only */ | ||
| double cache_size; /* in MB */ | ||
| double eps; /* stopping criteria */ | ||
| double C; /* for C_SVC, EPSILON_SVR and NU_SVR */ | ||
| int nr_weight; /* for C_SVC */ | ||
| int *weight_label; /* for C_SVC */ | ||
| double* weight; /* for C_SVC */ | ||
| double nu; /* for NU_SVC, ONE_CLASS, and NU_SVR */ | ||
| double p; /* for EPSILON_SVR */ | ||
| int shrinking; /* use the shrinking heuristics */ | ||
| int probability; /* do probability estimates */ | ||
| }; | ||
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| // | ||
| // svm_model | ||
| // | ||
| struct svm_model | ||
| { | ||
| struct svm_parameter param; /* parameter */ | ||
| int nr_class; /* number of classes, = 2 in regression/one class svm */ | ||
| int l; /* total #SV */ | ||
| struct svm_node **SV; /* SVs (SV[l]) */ | ||
| double **sv_coef; /* coefficients for SVs in decision functions (sv_coef[k-1][l]) */ | ||
| double *rho; /* constants in decision functions (rho[k*(k-1)/2]) */ | ||
| double *probA; /* pariwise probability information */ | ||
| double *probB; | ||
| int *sv_indices; /* sv_indices[0,...,nSV-1] are values in [1,...,num_traning_data] to indicate SVs in the training set */ | ||
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| /* for classification only */ | ||
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| int *label; /* label of each class (label[k]) */ | ||
| int *nSV; /* number of SVs for each class (nSV[k]) */ | ||
| /* nSV[0] + nSV[1] + ... + nSV[k-1] = l */ | ||
| /* XXX */ | ||
| int free_sv; /* 1 if svm_model is created by svm_load_model*/ | ||
| /* 0 if svm_model is created by svm_train */ | ||
| }; | ||
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| struct svm_model *svm_train(const struct svm_problem *prob, const struct svm_parameter *param); | ||
| void svm_cross_validation(const struct svm_problem *prob, const struct svm_parameter *param, int nr_fold, double *target); | ||
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| int svm_save_model(const char *model_file_name, const struct svm_model *model); | ||
| struct svm_model *svm_load_model(const char *model_file_name); | ||
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| int svm_get_svm_type(const struct svm_model *model); | ||
| int svm_get_nr_class(const struct svm_model *model); | ||
| void svm_get_labels(const struct svm_model *model, int *label); | ||
| void svm_get_sv_indices(const struct svm_model *model, int *sv_indices); | ||
| int svm_get_nr_sv(const struct svm_model *model); | ||
| double svm_get_svr_probability(const struct svm_model *model); | ||
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| double svm_predict_values(const struct svm_model *model, const struct svm_node *x, double* dec_values); | ||
| double svm_predict(const struct svm_model *model, const struct svm_node *x); | ||
| double svm_predict_probability(const struct svm_model *model, const struct svm_node *x, double* prob_estimates); | ||
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| void svm_free_model_content(struct svm_model *model_ptr); | ||
| void svm_free_and_destroy_model(struct svm_model **model_ptr_ptr); | ||
| void svm_destroy_param(struct svm_parameter *param); | ||
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| const char *svm_check_parameter(const struct svm_problem *prob, const struct svm_parameter *param); | ||
| int svm_check_probability_model(const struct svm_model *model); | ||
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| void svm_set_print_string_function(void (*print_func)(const char *)); | ||
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| #ifdef __cplusplus | ||
| } | ||
| #endif | ||
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| #endif /* _LIBSVM_H */ |