00001
00002
00003
00004
00005
00006
00007
00008
00009
00010
00011
00012
00013
00014
00015 #include <shogun/lib/config.h>
00016 #include <shogun/lib/common.h>
00017 #include <shogun/io/SGIO.h>
00018 #include <shogun/io/File.h>
00019 #include <shogun/lib/Time.h>
00020 #include <shogun/lib/Signal.h>
00021
00022 #include <shogun/base/Parallel.h>
00023
00024 #include <shogun/kernel/Kernel.h>
00025 #include <shogun/kernel/IdentityKernelNormalizer.h>
00026 #include <shogun/features/Features.h>
00027 #include <shogun/base/Parameter.h>
00028
00029 #include <shogun/classifier/svm/SVM.h>
00030
00031 #include <string.h>
00032 #include <unistd.h>
00033 #include <math.h>
00034
00035 #ifdef HAVE_PTHREAD
00036 #include <pthread.h>
00037 #endif
00038
00039 using namespace shogun;
00040
00041 CKernel::CKernel() : CSGObject()
00042 {
00043 init();
00044 register_params();
00045 }
00046
00047 CKernel::CKernel(int32_t size) : CSGObject()
00048 {
00049 init();
00050
00051 if (size<10)
00052 size=10;
00053
00054 cache_size=size;
00055 register_params();
00056 }
00057
00058
00059 CKernel::CKernel(CFeatures* p_lhs, CFeatures* p_rhs, int32_t size) : CSGObject()
00060 {
00061 init();
00062
00063 if (size<10)
00064 size=10;
00065
00066 cache_size=size;
00067
00068 set_normalizer(new CIdentityKernelNormalizer());
00069 init(p_lhs, p_rhs);
00070 register_params();
00071 }
00072
00073 CKernel::~CKernel()
00074 {
00075 if (get_is_initialized())
00076 SG_ERROR("Kernel still initialized on destruction.\n");
00077
00078 remove_lhs_and_rhs();
00079 SG_UNREF(normalizer);
00080
00081 SG_INFO("Kernel deleted (%p).\n", this);
00082 }
00083
00084 #ifdef USE_SVMLIGHT
00085 void CKernel::resize_kernel_cache(KERNELCACHE_IDX size, bool regression_hack)
00086 {
00087 if (size<10)
00088 size=10;
00089
00090 kernel_cache_cleanup();
00091 cache_size=size;
00092
00093 if (has_features() && get_num_vec_lhs())
00094 kernel_cache_init(cache_size, regression_hack);
00095 }
00096 #endif //USE_SVMLIGHT
00097
00098 bool CKernel::init(CFeatures* l, CFeatures* r)
00099 {
00100
00101 ASSERT(l);
00102 ASSERT(r);
00103
00104
00105 ASSERT(l->get_feature_class()==r->get_feature_class());
00106 ASSERT(l->get_feature_type()==r->get_feature_type());
00107
00108
00109 remove_lhs_and_rhs();
00110
00111
00112 SG_REF(l);
00113 if (l==r)
00114 lhs_equals_rhs=true;
00115 else
00116 SG_REF(r);
00117
00118 lhs=l;
00119 rhs=r;
00120
00121 ASSERT(!num_lhs || num_lhs==l->get_num_vectors());
00122 ASSERT(!num_rhs || num_rhs==l->get_num_vectors());
00123
00124 num_lhs=l->get_num_vectors();
00125 num_rhs=r->get_num_vectors();
00126
00127 return true;
00128 }
00129
00130 bool CKernel::set_normalizer(CKernelNormalizer* n)
00131 {
00132 SG_REF(n);
00133 if (lhs && rhs)
00134 n->init(this);
00135
00136 SG_UNREF(normalizer);
00137 normalizer=n;
00138
00139 return (normalizer!=NULL);
00140 }
00141
00142 CKernelNormalizer* CKernel::get_normalizer()
00143 {
00144 SG_REF(normalizer)
00145 return normalizer;
00146 }
00147
00148 bool CKernel::init_normalizer()
00149 {
00150 return normalizer->init(this);
00151 }
00152
00153 void CKernel::cleanup()
00154 {
00155 remove_lhs_and_rhs();
00156 }
00157
00158 #ifdef USE_SVMLIGHT
00159
00160
00161 void CKernel::kernel_cache_init(int32_t buffsize, bool regression_hack)
00162 {
00163 int32_t totdoc=get_num_vec_lhs();
00164 if (totdoc<=0)
00165 {
00166 SG_ERROR("kernel has zero rows: num_lhs=%d num_rhs=%d\n",
00167 get_num_vec_lhs(), get_num_vec_rhs());
00168 }
00169 uint64_t buffer_size=0;
00170 int32_t i;
00171
00172
00173 if (regression_hack)
00174 totdoc*=2;
00175
00176 buffer_size=((uint64_t) buffsize)*1024*1024/sizeof(KERNELCACHE_ELEM);
00177 if (buffer_size>((uint64_t) totdoc)*totdoc)
00178 buffer_size=((uint64_t) totdoc)*totdoc;
00179
00180 SG_INFO( "using a kernel cache of size %lld MB (%lld bytes) for %s Kernel\n", buffer_size*sizeof(KERNELCACHE_ELEM)/1024/1024, buffer_size*sizeof(KERNELCACHE_ELEM), get_name());
00181
00182
00183 ASSERT(buffer_size < (((uint64_t) 1) << (sizeof(KERNELCACHE_IDX)*8-1)));
00184
00185 kernel_cache.index = SG_MALLOC(int32_t, totdoc);
00186 kernel_cache.occu = SG_MALLOC(int32_t, totdoc);
00187 kernel_cache.lru = SG_MALLOC(int32_t, totdoc);
00188 kernel_cache.invindex = SG_MALLOC(int32_t, totdoc);
00189 kernel_cache.active2totdoc = SG_MALLOC(int32_t, totdoc);
00190 kernel_cache.totdoc2active = SG_MALLOC(int32_t, totdoc);
00191 kernel_cache.buffer = SG_MALLOC(KERNELCACHE_ELEM, buffer_size);
00192 kernel_cache.buffsize=buffer_size;
00193 kernel_cache.max_elems=(int32_t) (kernel_cache.buffsize/totdoc);
00194
00195 if(kernel_cache.max_elems>totdoc) {
00196 kernel_cache.max_elems=totdoc;
00197 }
00198
00199 kernel_cache.elems=0;
00200 for(i=0;i<totdoc;i++) {
00201 kernel_cache.index[i]=-1;
00202 kernel_cache.lru[i]=0;
00203 }
00204 for(i=0;i<totdoc;i++) {
00205 kernel_cache.occu[i]=0;
00206 kernel_cache.invindex[i]=-1;
00207 }
00208
00209 kernel_cache.activenum=totdoc;;
00210 for(i=0;i<totdoc;i++) {
00211 kernel_cache.active2totdoc[i]=i;
00212 kernel_cache.totdoc2active[i]=i;
00213 }
00214
00215 kernel_cache.time=0;
00216 }
00217
00218 void CKernel::get_kernel_row(
00219 int32_t docnum, int32_t *active2dnum, float64_t *buffer, bool full_line)
00220 {
00221 int32_t i,j;
00222 KERNELCACHE_IDX start;
00223
00224 int32_t num_vectors = get_num_vec_lhs();
00225 if (docnum>=num_vectors)
00226 docnum=2*num_vectors-1-docnum;
00227
00228
00229 if(kernel_cache.index[docnum] != -1)
00230 {
00231 kernel_cache.lru[kernel_cache.index[docnum]]=kernel_cache.time;
00232 start=((KERNELCACHE_IDX) kernel_cache.activenum)*kernel_cache.index[docnum];
00233
00234 if (full_line)
00235 {
00236 for(j=0;j<get_num_vec_lhs();j++)
00237 {
00238 if(kernel_cache.totdoc2active[j] >= 0)
00239 buffer[j]=kernel_cache.buffer[start+kernel_cache.totdoc2active[j]];
00240 else
00241 buffer[j]=(float64_t) kernel(docnum, j);
00242 }
00243 }
00244 else
00245 {
00246 for(i=0;(j=active2dnum[i])>=0;i++)
00247 {
00248 if(kernel_cache.totdoc2active[j] >= 0)
00249 buffer[j]=kernel_cache.buffer[start+kernel_cache.totdoc2active[j]];
00250 else
00251 {
00252 int32_t k=j;
00253 if (k>=num_vectors)
00254 k=2*num_vectors-1-k;
00255 buffer[j]=(float64_t) kernel(docnum, k);
00256 }
00257 }
00258 }
00259 }
00260 else
00261 {
00262 if (full_line)
00263 {
00264 for(j=0;j<get_num_vec_lhs();j++)
00265 buffer[j]=(KERNELCACHE_ELEM) kernel(docnum, j);
00266 }
00267 else
00268 {
00269 for(i=0;(j=active2dnum[i])>=0;i++)
00270 {
00271 int32_t k=j;
00272 if (k>=num_vectors)
00273 k=2*num_vectors-1-k;
00274 buffer[j]=(KERNELCACHE_ELEM) kernel(docnum, k);
00275 }
00276 }
00277 }
00278 }
00279
00280
00281
00282 void CKernel::cache_kernel_row(int32_t m)
00283 {
00284 register int32_t j,k,l;
00285 register KERNELCACHE_ELEM *cache;
00286
00287 int32_t num_vectors = get_num_vec_lhs();
00288
00289 if (m>=num_vectors)
00290 m=2*num_vectors-1-m;
00291
00292 if(!kernel_cache_check(m))
00293 {
00294 cache = kernel_cache_clean_and_malloc(m);
00295 if(cache) {
00296 l=kernel_cache.totdoc2active[m];
00297
00298 for(j=0;j<kernel_cache.activenum;j++)
00299 {
00300 k=kernel_cache.active2totdoc[j];
00301
00302 if((kernel_cache.index[k] != -1) && (l != -1) && (k != m)) {
00303 cache[j]=kernel_cache.buffer[((KERNELCACHE_IDX) kernel_cache.activenum)
00304 *kernel_cache.index[k]+l];
00305 }
00306 else
00307 {
00308 if (k>=num_vectors)
00309 k=2*num_vectors-1-k;
00310
00311 cache[j]=kernel(m, k);
00312 }
00313 }
00314 }
00315 else
00316 perror("Error: Kernel cache full! => increase cache size");
00317 }
00318 }
00319
00320
00321 void* CKernel::cache_multiple_kernel_row_helper(void* p)
00322 {
00323 int32_t j,k,l;
00324 S_KTHREAD_PARAM* params = (S_KTHREAD_PARAM*) p;
00325
00326 for (int32_t i=params->start; i<params->end; i++)
00327 {
00328 KERNELCACHE_ELEM* cache=params->cache[i];
00329 int32_t m = params->uncached_rows[i];
00330 l=params->kernel_cache->totdoc2active[m];
00331
00332 for(j=0;j<params->kernel_cache->activenum;j++)
00333 {
00334 k=params->kernel_cache->active2totdoc[j];
00335
00336 if((params->kernel_cache->index[k] != -1) && (l != -1) && (!params->needs_computation[k])) {
00337 cache[j]=params->kernel_cache->buffer[((KERNELCACHE_IDX) params->kernel_cache->activenum)
00338 *params->kernel_cache->index[k]+l];
00339 }
00340 else
00341 {
00342 if (k>=params->num_vectors)
00343 k=2*params->num_vectors-1-k;
00344
00345 cache[j]=params->kernel->kernel(m, k);
00346 }
00347 }
00348
00349
00350 params->needs_computation[m]=0;
00351 }
00352 return NULL;
00353 }
00354
00355
00356 void CKernel::cache_multiple_kernel_rows(int32_t* rows, int32_t num_rows)
00357 {
00358 #ifdef HAVE_PTHREAD
00359 if (parallel->get_num_threads()<2)
00360 {
00361 #endif
00362 for(int32_t i=0;i<num_rows;i++)
00363 cache_kernel_row(rows[i]);
00364 #ifdef HAVE_PTHREAD
00365 }
00366 else
00367 {
00368
00369 int32_t* uncached_rows = SG_MALLOC(int32_t, num_rows);
00370 KERNELCACHE_ELEM** cache = SG_MALLOC(KERNELCACHE_ELEM*, num_rows);
00371 pthread_t* threads = SG_MALLOC(pthread_t, parallel->get_num_threads()-1);
00372 S_KTHREAD_PARAM* params = SG_MALLOC(S_KTHREAD_PARAM, parallel->get_num_threads()-1);
00373 int32_t num_threads=parallel->get_num_threads()-1;
00374 int32_t num_vec=get_num_vec_lhs();
00375 ASSERT(num_vec>0);
00376 uint8_t* needs_computation=SG_MALLOC(uint8_t, num_vec);
00377 memset(needs_computation, 0, sizeof(uint8_t)*num_vec);
00378 int32_t step=0;
00379 int32_t num=0;
00380 int32_t end=0;
00381
00382
00383 for (int32_t i=0; i<num_rows; i++)
00384 {
00385 int32_t idx=rows[i];
00386 if (kernel_cache_check(idx))
00387 continue;
00388
00389 if (idx>=num_vec)
00390 idx=2*num_vec-1-idx;
00391
00392 needs_computation[idx]=1;
00393 uncached_rows[num]=idx;
00394 cache[num]= kernel_cache_clean_and_malloc(idx);
00395
00396 if (!cache[num])
00397 SG_ERROR("Kernel cache full! => increase cache size\n");
00398
00399 num++;
00400 }
00401
00402 if (num>0)
00403 {
00404 step= num/parallel->get_num_threads();
00405
00406 if (step<1)
00407 {
00408 num_threads=num-1;
00409 step=1;
00410 }
00411
00412 for (int32_t t=0; t<num_threads; t++)
00413 {
00414 params[t].kernel = this;
00415 params[t].kernel_cache = &kernel_cache;
00416 params[t].cache = cache;
00417 params[t].uncached_rows = uncached_rows;
00418 params[t].needs_computation = needs_computation;
00419 params[t].num_uncached = num;
00420 params[t].start = t*step;
00421 params[t].end = (t+1)*step;
00422 params[t].num_vectors = get_num_vec_lhs();
00423 end=params[t].end;
00424
00425 int code=pthread_create(&threads[t], NULL,
00426 CKernel::cache_multiple_kernel_row_helper, (void*)¶ms[t]);
00427
00428 if (!code)
00429 {
00430 SG_WARNING("Thread creation failed (thread %d of %d) "
00431 "with error:'%s'\n",t, num_threads, strerror(code));
00432 num_threads=t;
00433 end=t*step;
00434 break;
00435 }
00436 }
00437 }
00438 else
00439 num_threads=-1;
00440
00441
00442 S_KTHREAD_PARAM last_param;
00443 last_param.kernel = this;
00444 last_param.kernel_cache = &kernel_cache;
00445 last_param.cache = cache;
00446 last_param.uncached_rows = uncached_rows;
00447 last_param.needs_computation = needs_computation;
00448 last_param.start = end;
00449 last_param.num_uncached = num;
00450 last_param.end = num;
00451 last_param.num_vectors = get_num_vec_lhs();
00452
00453 cache_multiple_kernel_row_helper(&last_param);
00454
00455
00456 for (int32_t t=0; t<num_threads; t++)
00457 {
00458 if (pthread_join(threads[t], NULL) != 0)
00459 SG_WARNING("pthread_join of thread %d/%d failed\n", t, num_threads);
00460 }
00461
00462 SG_FREE(needs_computation);
00463 SG_FREE(params);
00464 SG_FREE(threads);
00465 SG_FREE(cache);
00466 SG_FREE(uncached_rows);
00467 }
00468 #endif
00469 }
00470
00471
00472
00473 void CKernel::kernel_cache_shrink(
00474 int32_t totdoc, int32_t numshrink, int32_t *after)
00475 {
00476 register int32_t i,j,jj,scount;
00477 KERNELCACHE_IDX from=0,to=0;
00478 int32_t *keep;
00479
00480 keep=SG_MALLOC(int32_t, totdoc);
00481 for(j=0;j<totdoc;j++) {
00482 keep[j]=1;
00483 }
00484 scount=0;
00485 for(jj=0;(jj<kernel_cache.activenum) && (scount<numshrink);jj++) {
00486 j=kernel_cache.active2totdoc[jj];
00487 if(!after[j]) {
00488 scount++;
00489 keep[j]=0;
00490 }
00491 }
00492
00493 for(i=0;i<kernel_cache.max_elems;i++) {
00494 for(jj=0;jj<kernel_cache.activenum;jj++) {
00495 j=kernel_cache.active2totdoc[jj];
00496 if(!keep[j]) {
00497 from++;
00498 }
00499 else {
00500 kernel_cache.buffer[to]=kernel_cache.buffer[from];
00501 to++;
00502 from++;
00503 }
00504 }
00505 }
00506
00507 kernel_cache.activenum=0;
00508 for(j=0;j<totdoc;j++) {
00509 if((keep[j]) && (kernel_cache.totdoc2active[j] != -1)) {
00510 kernel_cache.active2totdoc[kernel_cache.activenum]=j;
00511 kernel_cache.totdoc2active[j]=kernel_cache.activenum;
00512 kernel_cache.activenum++;
00513 }
00514 else {
00515 kernel_cache.totdoc2active[j]=-1;
00516 }
00517 }
00518
00519 kernel_cache.max_elems=
00520 (int32_t)(kernel_cache.buffsize/kernel_cache.activenum);
00521 if(kernel_cache.max_elems>totdoc) {
00522 kernel_cache.max_elems=totdoc;
00523 }
00524
00525 SG_FREE(keep);
00526
00527 }
00528
00529 void CKernel::kernel_cache_reset_lru()
00530 {
00531 int32_t maxlru=0,k;
00532
00533 for(k=0;k<kernel_cache.max_elems;k++) {
00534 if(maxlru < kernel_cache.lru[k])
00535 maxlru=kernel_cache.lru[k];
00536 }
00537 for(k=0;k<kernel_cache.max_elems;k++) {
00538 kernel_cache.lru[k]-=maxlru;
00539 }
00540 }
00541
00542 void CKernel::kernel_cache_cleanup()
00543 {
00544 SG_FREE(kernel_cache.index);
00545 SG_FREE(kernel_cache.occu);
00546 SG_FREE(kernel_cache.lru);
00547 SG_FREE(kernel_cache.invindex);
00548 SG_FREE(kernel_cache.active2totdoc);
00549 SG_FREE(kernel_cache.totdoc2active);
00550 SG_FREE(kernel_cache.buffer);
00551 memset(&kernel_cache, 0x0, sizeof(KERNEL_CACHE));
00552 }
00553
00554 int32_t CKernel::kernel_cache_malloc()
00555 {
00556 int32_t i;
00557
00558 if(kernel_cache_space_available()) {
00559 for(i=0;i<kernel_cache.max_elems;i++) {
00560 if(!kernel_cache.occu[i]) {
00561 kernel_cache.occu[i]=1;
00562 kernel_cache.elems++;
00563 return(i);
00564 }
00565 }
00566 }
00567 return(-1);
00568 }
00569
00570 void CKernel::kernel_cache_free(int32_t cacheidx)
00571 {
00572 kernel_cache.occu[cacheidx]=0;
00573 kernel_cache.elems--;
00574 }
00575
00576
00577
00578 int32_t CKernel::kernel_cache_free_lru()
00579 {
00580 register int32_t k,least_elem=-1,least_time;
00581
00582 least_time=kernel_cache.time+1;
00583 for(k=0;k<kernel_cache.max_elems;k++) {
00584 if(kernel_cache.invindex[k] != -1) {
00585 if(kernel_cache.lru[k]<least_time) {
00586 least_time=kernel_cache.lru[k];
00587 least_elem=k;
00588 }
00589 }
00590 }
00591
00592 if(least_elem != -1) {
00593 kernel_cache_free(least_elem);
00594 kernel_cache.index[kernel_cache.invindex[least_elem]]=-1;
00595 kernel_cache.invindex[least_elem]=-1;
00596 return(1);
00597 }
00598 return(0);
00599 }
00600
00601
00602
00603 KERNELCACHE_ELEM* CKernel::kernel_cache_clean_and_malloc(int32_t cacheidx)
00604 {
00605 int32_t result;
00606 if((result = kernel_cache_malloc()) == -1) {
00607 if(kernel_cache_free_lru()) {
00608 result = kernel_cache_malloc();
00609 }
00610 }
00611 kernel_cache.index[cacheidx]=result;
00612 if(result == -1) {
00613 return(0);
00614 }
00615 kernel_cache.invindex[result]=cacheidx;
00616 kernel_cache.lru[kernel_cache.index[cacheidx]]=kernel_cache.time;
00617 return &kernel_cache.buffer[((KERNELCACHE_IDX) kernel_cache.activenum)*kernel_cache.index[cacheidx]];
00618 }
00619 #endif //USE_SVMLIGHT
00620
00621 void CKernel::load(CFile* loader)
00622 {
00623 SG_SET_LOCALE_C;
00624 SG_RESET_LOCALE;
00625 }
00626
00627 void CKernel::save(CFile* writer)
00628 {
00629 SGMatrix<float64_t> k_matrix=get_kernel_matrix<float64_t>();
00630 SG_SET_LOCALE_C;
00631 writer->set_matrix(k_matrix.matrix, k_matrix.num_rows, k_matrix.num_cols);
00632 SG_FREE(k_matrix.matrix);
00633 SG_RESET_LOCALE;
00634 }
00635
00636 void CKernel::remove_lhs_and_rhs()
00637 {
00638 if (rhs!=lhs)
00639 SG_UNREF(rhs);
00640 rhs = NULL;
00641 num_rhs=0;
00642
00643 SG_UNREF(lhs);
00644 lhs = NULL;
00645 num_lhs=0;
00646 lhs_equals_rhs=false;
00647
00648 #ifdef USE_SVMLIGHT
00649 cache_reset();
00650 #endif //USE_SVMLIGHT
00651 }
00652
00653 void CKernel::remove_lhs()
00654 {
00655 if (rhs==lhs)
00656 rhs=NULL;
00657 SG_UNREF(lhs);
00658 lhs = NULL;
00659 num_lhs=0;
00660 lhs_equals_rhs=false;
00661 #ifdef USE_SVMLIGHT
00662 cache_reset();
00663 #endif //USE_SVMLIGHT
00664 }
00665
00667 void CKernel::remove_rhs()
00668 {
00669 if (rhs!=lhs)
00670 SG_UNREF(rhs);
00671 rhs = NULL;
00672 num_rhs=0;
00673 lhs_equals_rhs=false;
00674
00675 #ifdef USE_SVMLIGHT
00676 cache_reset();
00677 #endif //USE_SVMLIGHT
00678 }
00679
00680 #define ENUM_CASE(n) case n: SG_INFO(#n " "); break;
00681
00682 void CKernel::list_kernel()
00683 {
00684 SG_INFO( "%p - \"%s\" weight=%1.2f OPT:%s", this, get_name(),
00685 get_combined_kernel_weight(),
00686 get_optimization_type()==FASTBUTMEMHUNGRY ? "FASTBUTMEMHUNGRY" :
00687 "SLOWBUTMEMEFFICIENT");
00688
00689 switch (get_kernel_type())
00690 {
00691 ENUM_CASE(K_UNKNOWN)
00692 ENUM_CASE(K_LINEAR)
00693 ENUM_CASE(K_POLY)
00694 ENUM_CASE(K_GAUSSIAN)
00695 ENUM_CASE(K_GAUSSIANSHIFT)
00696 ENUM_CASE(K_GAUSSIANMATCH)
00697 ENUM_CASE(K_HISTOGRAM)
00698 ENUM_CASE(K_SALZBERG)
00699 ENUM_CASE(K_LOCALITYIMPROVED)
00700 ENUM_CASE(K_SIMPLELOCALITYIMPROVED)
00701 ENUM_CASE(K_FIXEDDEGREE)
00702 ENUM_CASE(K_WEIGHTEDDEGREE)
00703 ENUM_CASE(K_WEIGHTEDDEGREEPOS)
00704 ENUM_CASE(K_WEIGHTEDDEGREERBF)
00705 ENUM_CASE(K_WEIGHTEDCOMMWORDSTRING)
00706 ENUM_CASE(K_POLYMATCH)
00707 ENUM_CASE(K_ALIGNMENT)
00708 ENUM_CASE(K_COMMWORDSTRING)
00709 ENUM_CASE(K_COMMULONGSTRING)
00710 ENUM_CASE(K_SPECTRUMRBF)
00711 ENUM_CASE(K_COMBINED)
00712 ENUM_CASE(K_AUC)
00713 ENUM_CASE(K_CUSTOM)
00714 ENUM_CASE(K_SIGMOID)
00715 ENUM_CASE(K_CHI2)
00716 ENUM_CASE(K_DIAG)
00717 ENUM_CASE(K_CONST)
00718 ENUM_CASE(K_DISTANCE)
00719 ENUM_CASE(K_LOCALALIGNMENT)
00720 ENUM_CASE(K_PYRAMIDCHI2)
00721 ENUM_CASE(K_OLIGO)
00722 ENUM_CASE(K_MATCHWORD)
00723 ENUM_CASE(K_TPPK)
00724 ENUM_CASE(K_REGULATORYMODULES)
00725 ENUM_CASE(K_SPARSESPATIALSAMPLE)
00726 ENUM_CASE(K_HISTOGRAMINTERSECTION)
00727 ENUM_CASE(K_WAVELET)
00728 ENUM_CASE(K_WAVE)
00729 ENUM_CASE(K_CAUCHY)
00730 ENUM_CASE(K_TSTUDENT)
00731 ENUM_CASE(K_MULTIQUADRIC)
00732 ENUM_CASE(K_EXPONENTIAL)
00733 ENUM_CASE(K_RATIONAL_QUADRATIC)
00734 ENUM_CASE(K_POWER)
00735 ENUM_CASE(K_SPHERICAL)
00736 ENUM_CASE(K_LOG)
00737 ENUM_CASE(K_SPLINE)
00738 ENUM_CASE(K_ANOVA)
00739 ENUM_CASE(K_CIRCULAR)
00740 ENUM_CASE(K_INVERSEMULTIQUADRIC)
00741 ENUM_CASE(K_SPECTRUMMISMATCHRBF)
00742 ENUM_CASE(K_DISTANTSEGMENTS)
00743 ENUM_CASE(K_BESSEL)
00744 }
00745
00746 switch (get_feature_class())
00747 {
00748 ENUM_CASE(C_UNKNOWN)
00749 ENUM_CASE(C_SIMPLE)
00750 ENUM_CASE(C_SPARSE)
00751 ENUM_CASE(C_STRING)
00752 ENUM_CASE(C_STREAMING_SIMPLE)
00753 ENUM_CASE(C_STREAMING_SPARSE)
00754 ENUM_CASE(C_STREAMING_STRING)
00755 ENUM_CASE(C_STREAMING_VW)
00756 ENUM_CASE(C_COMBINED)
00757 ENUM_CASE(C_COMBINED_DOT)
00758 ENUM_CASE(C_WD)
00759 ENUM_CASE(C_SPEC)
00760 ENUM_CASE(C_WEIGHTEDSPEC)
00761 ENUM_CASE(C_POLY)
00762 ENUM_CASE(C_ANY)
00763 }
00764
00765 switch (get_feature_type())
00766 {
00767 ENUM_CASE(F_UNKNOWN)
00768 ENUM_CASE(F_BOOL)
00769 ENUM_CASE(F_CHAR)
00770 ENUM_CASE(F_BYTE)
00771 ENUM_CASE(F_SHORT)
00772 ENUM_CASE(F_WORD)
00773 ENUM_CASE(F_INT)
00774 ENUM_CASE(F_UINT)
00775 ENUM_CASE(F_LONG)
00776 ENUM_CASE(F_ULONG)
00777 ENUM_CASE(F_SHORTREAL)
00778 ENUM_CASE(F_DREAL)
00779 ENUM_CASE(F_LONGREAL)
00780 ENUM_CASE(F_ANY)
00781 }
00782 SG_INFO( "\n");
00783 }
00784 #undef ENUM_CASE
00785
00786 bool CKernel::init_optimization(
00787 int32_t count, int32_t *IDX, float64_t * weights)
00788 {
00789 SG_ERROR( "kernel does not support linadd optimization\n");
00790 return false ;
00791 }
00792
00793 bool CKernel::delete_optimization()
00794 {
00795 SG_ERROR( "kernel does not support linadd optimization\n");
00796 return false;
00797 }
00798
00799 float64_t CKernel::compute_optimized(int32_t vector_idx)
00800 {
00801 SG_ERROR( "kernel does not support linadd optimization\n");
00802 return 0;
00803 }
00804
00805 void CKernel::compute_batch(
00806 int32_t num_vec, int32_t* vec_idx, float64_t* target, int32_t num_suppvec,
00807 int32_t* IDX, float64_t* weights, float64_t factor)
00808 {
00809 SG_ERROR( "kernel does not support batch computation\n");
00810 }
00811
00812 void CKernel::add_to_normal(int32_t vector_idx, float64_t weight)
00813 {
00814 SG_ERROR( "kernel does not support linadd optimization, add_to_normal not implemented\n");
00815 }
00816
00817 void CKernel::clear_normal()
00818 {
00819 SG_ERROR( "kernel does not support linadd optimization, clear_normal not implemented\n");
00820 }
00821
00822 int32_t CKernel::get_num_subkernels()
00823 {
00824 return 1;
00825 }
00826
00827 void CKernel::compute_by_subkernel(
00828 int32_t vector_idx, float64_t * subkernel_contrib)
00829 {
00830 SG_ERROR( "kernel compute_by_subkernel not implemented\n");
00831 }
00832
00833 const float64_t* CKernel::get_subkernel_weights(int32_t &num_weights)
00834 {
00835 num_weights=1 ;
00836 return &combined_kernel_weight ;
00837 }
00838
00839 void CKernel::set_subkernel_weights(float64_t* weights, int32_t num_weights)
00840 {
00841 combined_kernel_weight = weights[0] ;
00842 if (num_weights!=1)
00843 SG_ERROR( "number of subkernel weights should be one ...\n");
00844 }
00845
00846 bool CKernel::init_optimization_svm(CSVM * svm)
00847 {
00848 int32_t num_suppvec=svm->get_num_support_vectors();
00849 int32_t* sv_idx=SG_MALLOC(int32_t, num_suppvec);
00850 float64_t* sv_weight=SG_MALLOC(float64_t, num_suppvec);
00851
00852 for (int32_t i=0; i<num_suppvec; i++)
00853 {
00854 sv_idx[i] = svm->get_support_vector(i);
00855 sv_weight[i] = svm->get_alpha(i);
00856 }
00857 bool ret = init_optimization(num_suppvec, sv_idx, sv_weight);
00858
00859 SG_FREE(sv_idx);
00860 SG_FREE(sv_weight);
00861 return ret;
00862 }
00863
00864 void CKernel::load_serializable_post() throw (ShogunException)
00865 {
00866 CSGObject::load_serializable_post();
00867 if (lhs_equals_rhs)
00868 rhs=lhs;
00869 }
00870
00871 void CKernel::save_serializable_pre() throw (ShogunException)
00872 {
00873 CSGObject::save_serializable_pre();
00874
00875 if (lhs_equals_rhs)
00876 rhs=NULL;
00877 }
00878
00879 void CKernel::save_serializable_post() throw (ShogunException)
00880 {
00881 CSGObject::save_serializable_post();
00882
00883 if (lhs_equals_rhs)
00884 rhs=lhs;
00885 }
00886
00887 void CKernel::register_params() {
00888 m_parameters->add(&cache_size, "cache_size",
00889 "Cache size in MB.");
00890 m_parameters->add((CSGObject**) &lhs, "lhs",
00891 "Feature vectors to occur on left hand side.");
00892 m_parameters->add((CSGObject**) &rhs, "rhs",
00893 "Feature vectors to occur on right hand side.");
00894 m_parameters->add(&lhs_equals_rhs, "lhs_equals_rhs",
00895 "If features on lhs are the same as on rhs.");
00896 m_parameters->add(&num_lhs, "num_lhs",
00897 "Number of feature vectors on left hand side.");
00898 m_parameters->add(&num_rhs, "num_rhs",
00899 "Number of feature vectors on right hand side.");
00900 m_parameters->add(&combined_kernel_weight, "combined_kernel_weight",
00901 "Combined kernel weight.");
00902 m_parameters->add(&optimization_initialized,
00903 "optimization_initialized",
00904 "Optimization is initialized.");
00905 m_parameters->add((machine_int_t*) &opt_type, "opt_type",
00906 "Optimization type.");
00907 m_parameters->add(&properties, "properties",
00908 "Kernel properties.");
00909 m_parameters->add((CSGObject**) &normalizer, "normalizer",
00910 "Normalize the kernel.");
00911 }
00912
00913
00914 void CKernel::init()
00915 {
00916 cache_size=10;
00917 kernel_matrix=NULL;
00918 lhs=NULL;
00919 rhs=NULL;
00920 num_lhs=0;
00921 num_rhs=0;
00922 combined_kernel_weight=1;
00923 optimization_initialized=false;
00924 opt_type=FASTBUTMEMHUNGRY;
00925 properties=KP_NONE;
00926 normalizer=NULL;
00927
00928 #ifdef USE_SVMLIGHT
00929 memset(&kernel_cache, 0x0, sizeof(KERNEL_CACHE));
00930 #endif //USE_SVMLIGHT
00931
00932 set_normalizer(new CIdentityKernelNormalizer());
00933 }