Commit Inicial

data/tanveer/libras/conxuntos.dat

@@ -0,0 +1,2 @@
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data/tanveer/libras/conxuntos_kfold.dat

@@ -0,0 +1,8 @@
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data/tanveer/libras/le_datos.m

@@ -0,0 +1,23 @@
+printf('lendo problema %s ...\n', problema);
+
+n_entradas= 90; n_clases= 15; n_fich= 1; fich{1}= 'movement_libras.data'; n_patrons(1)= 360;
+
+n_max= max(n_patrons);
+x = zeros(n_fich, n_max, n_entradas); cl= zeros(n_fich, n_max);
+
+n_patrons_total = sum(n_patrons); n_iter=0;
+
+for i_fich=1:n_fich
+  f=fopen(fich{i_fich}, 'r');
+  if -1==f
+	error('erro en fopen abrindo %s\n', fich{i_fich});
+  end
+  for i=1:n_patrons(i_fich)
+  	fprintf(2,'%5.1f%%\r', 100*n_iter++/n_patrons_total);
+	for j = 1:n_entradas
+	  x(i_fich,i,j) = fscanf(f,'%g',1);
+	end	
+	cl(i_fich,i) = fscanf(f,'%i',1) - 1;  	% lectura da clase
+  end
+  fclose(f);
+end

data/tanveer/libras/libras.arff

@@ -0,0 +1,453 @@
+@relation libras
+@attribute 'f1' real
+@attribute 'f2' real
+@attribute 'f3' real
+@attribute 'f4' real
+@attribute 'f5' real
+@attribute 'f6' real
+@attribute 'f7' real
+@attribute 'f8' real
+@attribute 'f9' real
+@attribute 'f10' real
+@attribute 'f11' real
+@attribute 'f12' real
+@attribute 'f13' real
+@attribute 'f14' real
+@attribute 'f15' real
+@attribute 'f16' real
+@attribute 'f17' real
+@attribute 'f18' real
+@attribute 'f19' real
+@attribute 'f20' real
+@attribute 'f21' real
+@attribute 'f22' real
+@attribute 'f23' real
+@attribute 'f24' real
+@attribute 'f25' real
+@attribute 'f26' real
+@attribute 'f27' real
+@attribute 'f28' real
+@attribute 'f29' real
+@attribute 'f30' real
+@attribute 'f31' real
+@attribute 'f32' real
+@attribute 'f33' real
+@attribute 'f34' real
+@attribute 'f35' real
+@attribute 'f36' real
+@attribute 'f37' real
+@attribute 'f38' real
+@attribute 'f39' real
+@attribute 'f40' real
+@attribute 'f41' real
+@attribute 'f42' real
+@attribute 'f43' real
+@attribute 'f44' real
+@attribute 'f45' real
+@attribute 'f46' real
+@attribute 'f47' real
+@attribute 'f48' real
+@attribute 'f49' real
+@attribute 'f50' real
+@attribute 'f51' real
+@attribute 'f52' real
+@attribute 'f53' real
+@attribute 'f54' real
+@attribute 'f55' real
+@attribute 'f56' real
+@attribute 'f57' real
+@attribute 'f58' real
+@attribute 'f59' real
+@attribute 'f60' real
+@attribute 'f61' real
+@attribute 'f62' real
+@attribute 'f63' real
+@attribute 'f64' real
+@attribute 'f65' real
+@attribute 'f66' real
+@attribute 'f67' real
+@attribute 'f68' real
+@attribute 'f69' real
+@attribute 'f70' real
+@attribute 'f71' real
+@attribute 'f72' real
+@attribute 'f73' real
+@attribute 'f74' real
+@attribute 'f75' real
+@attribute 'f76' real
+@attribute 'f77' real
+@attribute 'f78' real
+@attribute 'f79' real
+@attribute 'f80' real
+@attribute 'f81' real
+@attribute 'f82' real
+@attribute 'f83' real
+@attribute 'f84' real
+@attribute 'f85' real
+@attribute 'f86' real
+@attribute 'f87' real
+@attribute 'f88' real
+@attribute 'f89' real
+@attribute 'f90' real
+@attribute 'clase' {0,1,2,3,4,5,6,7,8,9,10,11,12,13,14}
+@data
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data/tanveer/libras/libras.cost

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+ 1.0	 1.0	 1.0	 1.0	 1.0	 1.0	 1.0	 1.0	 1.0	 1.0	 1.0	 1.0	 1.0	 1.0	 0.0	

data/tanveer/libras/libras.txt

@@ -0,0 +1,8 @@
+n_entradas= 90
+n_clases= 15
+n_arquivos= 1
+fich1= libras_R.dat
+n_patrons1= 360
+n_patrons_entrena= 180
+n_patrons_valida= 180
+n_conxuntos= 1

data/tanveer/libras/libras_R.dat

@@ -0,0 +1,361 @@
+	f1	f2	f3	f4	f5	f6	f7	f8	f9	f10	f11	f12	f13	f14	f15	f16	f17	f18	f19	f20	f21	f22	f23	f24	f25	f26	f27	f28	f29	f30	f31	f32	f33	f34	f35	f36	f37	f38	f39	f40	f41	f42	f43	f44	f45	f46	f47	f48	f49	f50	f51	f52	f53	f54	f55	f56	f57	f58	f59	f60	f61	f62	f63	f64	f65	f66	f67	f68	f69	f70	f71	f72	f73	f74	f75	f76	f77	f78	f79	f80	f81	f82	f83	f84	f85	f86	f87	f88	f89	f90	clase
+1	1.15776	-0.928219	1.16251	-0.951144	1.17859	-0.947486	1.17419	-0.93986	1.10313	-1.04577	0.928276	-1.17441	0.652756	-1.2994	0.259003	-1.32689	-0.221988	-1.14837	-0.608225	-0.78001	-0.915832	-0.308568	-1.17522	0.418315	-1.25294	1.30602	-1.2477	1.9038	-1.23979	1.89193	-1.22581	1.39229	-1.18655	0.676955	-0.997242	0.0413943	-0.698135	-0.51645	-0.308727	-0.920144	0.21575	-1.23548	0.682894	-1.37649	1.02175	-1.38702	1.25934	-1.29567	1.40202	-1.10198	1.45716	-1.04109	1.36631	-1.11729	1.09691	-1.40678	0.67179	-1.54903	0.177544	-1.43935	-0.357719	-1.09571	-0.805969	-0.602645	-1.11361	0.153015	-1.13932	0.906016	-1.023	1.48786	-0.892049	1.97981	-0.853953	2.21446	-0.87301	1.98718	-0.914243	1.46106	-0.876373	0.822918	-0.702427	0.226287	-0.422997	-0.247607	-0.0674604	-0.581063	0.314194	-0.820356	0.647092	-0.889723	0
+2	0.564595	-1.50848	0.577256	-1.5072	0.582269	-1.50429	0.591847	-1.49753	0.601172	-1.5065	0.549208	-1.55107	0.45427	-1.59425	0.290735	-1.62921	0.0213888	-1.64814	-0.305016	-1.56704	-0.658421	-1.37582	-0.95173	-1.08349	-1.22261	-0.629572	-1.49162	-0.0896178	-1.67405	0.515777	-1.82115	1.02112	-1.98517	1.45063	-2.10854	1.71383	-2.16673	1.64996	-2.13127	1.23977	-1.98504	0.620035	-1.65636	-0.111661	-1.29091	-0.778969	-0.861082	-1.32858	-0.419487	-1.68892	0.0105016	-1.88137	0.445007	-1.9433	0.837073	-1.79542	1.11034	-1.58126	1.3124	-1.35985	1.35822	-1.31583	1.26847	-1.39689	1.07149	-1.56345	0.77575	-1.66568	0.405742	-1.68978	-0.00176261	-1.59612	-0.356971	-1.34637	-0.678516	-0.959481	-0.960463	-0.472269	-1.20998	0.0431932	-1.39798	0.574783	-1.4736	0.958294	-1.48132	1.16837	-1.46306	1.23856	-1.42003	1.19668	0
+3	0.778505	-1.70604	0.791824	-1.70493	0.797316	-1.7023	0.808974	-1.69584	0.832037	-1.68084	0.825842	-1.67656	0.652756	-1.70966	0.248443	-1.70809	-0.221988	-1.58062	-0.545464	-1.20803	-0.802563	-0.765969	-1.06345	-0.0776639	-1.18214	0.696961	-1.2375	1.2529	-1.25016	1.56169	-1.28957	1.63498	-1.26419	1.25722	-1.13615	0.382102	-0.757827	-0.484588	-0.260429	-1.0491	0.335343	-1.39677	0.881717	-1.48997	1.29382	-1.56776	1.60169	-1.54244	1.71649	-1.49332	1.62863	-1.54203	1.34493	-1.68415	0.858735	-1.77926	0.222242	-1.80685	-0.289768	-1.39166	-0.647415	-0.828445	-0.93698	-0.151031	-1.06083	0.582098	-1.10878	1.05468	-1.09197	1.31608	-1.04522	1.36087	-0.975883	1.09919	-0.845239	0.507197	-0.572211	-0.112272	-0.2185	-0.602145	0.160029	-0.980129	0.526259	-1.20178	0.856978	-1.19015	1.11885	-1.07146	1.28179	-0.974615	0
+4	-0.00911567	-1.23688	-0.0177345	-1.23536	-0.0238062	-1.23209	-0.0299878	-1.22491	-0.0213001	-1.20768	-0.0449482	-1.26227	-0.172565	-1.38917	-0.439445	-1.47146	-0.803925	-1.39148	-1.17286	-1.1528	-1.4718	-0.738246	-1.7543	-0.353241	-2.00144	0.317935	-2.08114	1.03591	-2.11865	1.52037	-2.18265	1.53507	-2.30687	1.19771	-2.32849	0.645343	-2.22649	0.0410324	-2.01058	-0.549424	-1.66206	-1.00958	-1.21191	-1.44128	-0.656095	-1.83072	-0.132197	-2.01955	0.306987	-1.93355	0.599867	-1.70364	0.755671	-1.6032	0.761283	-1.64969	0.627918	-1.77462	0.311054	-1.82115	-0.157139	-1.77177	-0.674958	-1.53702	-1.0819	-1.14966	-1.33287	-0.684614	-1.47622	-0.329964	-1.5621	0.0267556	-1.61356	0.467624	-1.66023	0.800499	-1.66312	0.767733	-1.56208	0.433056	-1.35162	0.0922279	-1.06808	-0.260889	-0.729079	-0.658822	-0.36662	-0.996131	-0.00477194	-1.15656	0
+5	0.525684	-0.915844	0.528493	-0.901709	0.543151	-0.897984	0.552351	-0.90265	0.571017	-0.908812	0.528711	-0.960997	0.339338	-0.978907	0.0579377	-0.787942	-0.243158	-0.391884	-0.33637	0.0484126	-0.308393	0.66168	-0.199901	1.25874	0.213713	2.90323	-0.0991847	1.78178	-0.247266	1.20386	-0.237015	0.564233	-0.154926	-0.0967154	0.0794063	-0.779301	0.41225	-1.40852	0.89823	-1.80663	1.4956	-1.71949	1.98117	-1.18189	2.14409	-0.499615	2.05446	-0.292124	1.95501	-0.547643	1.85367	-0.992648	1.74128	-1.42507	1.49752	-1.86021	1.06647	-1.98406	0.54471	-1.7257	0.121439	-1.26863	-0.150858	-0.742845	-0.290245	-0.291428	-0.314213	0.147852	-0.333259	0.72927	-0.231547	1.48464	-0.160039	1.98604	0.117942	2.82722	0.102676	2.78107	-0.0702836	1.95214	-0.108901	1.67401	-0.220214	0.9848	-0.176215	0.429748	-0.0571385	-0.117312	0.175311	-0.634995	0
+6	1.34251	-1.05164	1.3673	-0.951144	1.33501	-0.910333	1.36172	-0.93986	1.39425	-0.709566	1.27657	-0.220319	0.955695	0.226132	0.4918	0.605391	0.0425044	0.85095	-0.305016	0.821603	-0.504006	0.606234	-0.535162	0.266778	-0.474067	-0.155818	-0.373583	-0.59137	-0.257582	-0.95669	-0.183862	-1.07757	-0.210438	-0.855475	-0.198419	-0.438593	-0.0414601	-0.0226228	0.23441	0.30489	0.670254	0.458676	1.18582	0.4072	1.62257	0.190572	1.87775	-0.259218	1.96583	-0.906306	1.93938	-1.47739	1.95557	-1.81373	2.01719	-1.56867	2.04226	-0.95286	1.94665	-0.341794	1.62562	0.0834375	1.13746	0.425109	0.564824	0.689419	0.0219503	0.697884	-0.293831	0.299826	-0.37512	-0.262064	-0.310089	-0.741687	-0.196925	-0.98615	-0.156142	-0.778929	-0.125853	-0.266002	0.0209374	0.212852	0.33272	0.521023	0.739133	0.637049	1.17192	0.560622	1.53052	0.323287	0
+7	0.749347	0.66455	0.743061	0.667744	0.728885	0.723047	0.749781	0.696098	0.791916	0.585425	0.815567	0.608272	0.75721	0.251773	0.56588	-0.0387207	0.35995	-0.13517	0.0609533	-0.0344356	-0.339265	0.0656637	-0.768841	0.211662	-0.949478	0.791688	-1.27817	1.33427	-1.47761	1.79562	-1.55539	1.92054	-1.55259	1.6887	-1.49502	1.0015	-1.17573	0.630446	-0.960504	0.320975	-0.382279	-0.0415006	0.250116	-0.160276	0.670321	-0.401007	1.00532	-0.209822	1.23941	0.267588	1.41433	0.60713	1.51629	0.745186	1.48666	0.601408	1.29671	0.239479	0.945238	-0.405427	0.511366	-0.278164	0.0347356	-0.119883	-0.532991	0.0610548	-0.843921	0.430285	-1.01312	0.543147	-1.13134	1.08584	-1.22905	1.47539	-1.262	1.57384	-1.2286	1.47442	-1.14512	1.14553	-0.887931	0.789277	-0.634927	0.613767	-0.366548	0.326069	0.00475786	0.121213	0.295396	0.104979	0
+8	1.05078	0.257104	1.05521	0.259939	1.08085	0.228088	0.976807	-0.0723031	0.751743	-0.560186	0.436553	-0.785224	-0.0576324	-0.55585	-0.64051	-0.248995	-0.888606	0.107946	-1.07874	0.55928	-1.08057	1.32697	-1.04312	1.49295	-1.00005	1.44139	-0.983439	0.832517	-0.784903	0.391942	-0.641019	0.107403	-0.310222	-0.126474	0.195157	-0.283793	0.686883	-0.309381	0.98272	-0.43662	1.20849	-0.0737723	1.3379	0.131553	1.30519	0.897228	1.33665	0.875956	1.29361	0.528485	1.21073	-0.184696	1.04495	-0.323744	0.772086	-0.548418	0.43055	-0.550054	-0.000487438	-0.596256	-0.435716	-0.40395	-0.816863	-0.119883	-0.934166	0.26027	-1.02725	0.608684	-1.06238	1.20157	-0.987764	1.69099	-0.994646	1.4217	-0.937842	0.787193	-0.766313	0.44771	-0.570646	0.217943	-0.146011	-0.0954548	0.277403	-0.0886258	0.594158	0.0668724	0.791673	0.0207699	0.973024	0.371812	0
+9	1.06048	0.417597	1.05521	0.420573	1.05148	0.339493	0.986656	-0.245825	0.781846	-0.771858	0.487769	-0.860555	0.0468221	-0.940472	-0.460618	-0.76165	-0.814537	-0.499903	-0.984628	-0.186294	-1.01878	0.148833	-1.05331	0.390758	-1.11133	0.669887	-1.06473	1.36139	-1.09504	1.32775	-1.06629	0.535677	-0.875954	0.111598	-0.453142	-0.33022	0.0898997	-0.580174	0.548223	-0.484945	0.885571	-0.428761	1.11567	-0.387309	1.38455	0.00982533	1.66792	0.316613	1.83572	0.626321	1.83223	0.542489	1.67703	0.194559	1.34594	-0.386456	0.891037	-0.775645	0.4112	-0.596256	-0.0791418	-0.624008	-0.554842	-0.431364	-0.891926	0.0150414	-1.06801	0.326251	-1.34816	0.586122	-1.55255	1.08584	-1.58539	1.27385	-1.50279	1.21384	-1.20083	0.541079	-0.793019	0.271721	-0.498416	-0.0283963	-0.109627	-0.18137	0.331291	-0.127497	0.650235	-0.00434079	0.835778	0.104979	0
+10	0.895188	0.158323	0.899133	0.185788	0.91467	0.153837	0.868218	0.0268524	0.771829	-0.410751	0.518489	-0.596922	0.203558	-0.466133	-0.23838	-0.433036	-0.68757	-0.256787	-0.88008	0.131261	-1.09085	0.315171	-1.24634	1.01078	-1.33384	1.25188	-1.29851	1.28002	-1.25016	1.01124	-1.03441	0.549986	-0.798305	0.0371681	-0.256294	-0.25282	0.197308	-0.197898	0.64482	-0.194789	0.945368	-0.251232	1.20922	0.293719	1.33919	0.732881	1.34767	0.875956	1.30449	0.821993	1.21073	0.477847	1.00209	-0.210331	0.653028	-0.499864	0.112618	-0.59836	-0.512264	-0.484933	-1.07081	-0.341057	-1.47197	0.0980869	-1.59915	0.85798	-1.67925	1.45605	-1.67331	1.77416	-1.60041	1.69099	-1.46351	1.38136	-1.28977	0.760524	-1.02518	0.234419	-0.579892	-0.0912522	-0.0810921	-0.0954548	0.360355	-0.075344	0.630378	-0.0627259	0.800542	0.0961019	0.990186	0.396074	0
+11	1.11885	-0.0886306	1.1137	-0.0242806	1.11991	-0.0936161	1.13469	0.0268524	1.1433	-0.186599	1.06143	-0.458842	0.872142	-0.658416	0.544706	-0.735359	0.148356	-0.635	-0.305016	-0.476233	-0.545205	-0.266953	-0.799305	0.101432	-0.959623	0.453301	-1.09521	0.913887	-1.11573	1.08002	-1.14072	0.921149	-1.20874	0.111598	-0.742519	-0.578007	-0.0175709	-0.946553	0.681012	-0.823426	1.12476	-1.3323	1.38464	-0.581908	1.47522	-0.00664487	1.60169	0.34952	1.65141	0.544826	1.65007	0.526363	1.60203	0.37269	1.43253	-0.418848	1.14322	-1.03339	0.722742	-1.23258	0.110263	-1.17429	-0.434725	-1.06987	-0.891926	-0.904432	-1.14954	-0.521049	-1.25947	0.056505	-1.28451	0.673198	-1.32286	1.13947	-1.34536	1.37385	-1.33026	1.36775	-1.32117	1.29339	-1.24034	0.896524	-1.10496	0.295689	-0.756256	-0.0627259	-0.242828	-0.267976	0.175311	-0.295323	0
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data/tanveer/libras/movement_libras.names

@@ -0,0 +1,112 @@
+1. Title: LIBRAS Movement Database
+
+2. Sources:
+
+     (a) Creators: 
+		Daniel Baptista Dias (Dias, D.B.)
+            Sarajane Marques Peres (Peres, S. M.)
+		Helton Hideraldo B<>scaro (B<>scaro. H. H.)
+        {danielbdias,heltonhb, sarajane} at usp.br
+
+     (b) Donor: 
+		University of S<>o Paulo
+		School of Art, Sciences and Humanities
+		S<>o Paulo, SP, Brazil
+		http://each.uspnet.usp.br/each/
+			
+     (c) Date: November, 2008
+
+
+3. Past Usage:
+
+   1. DIAS, D. B.; MADEO, R. C. B.; ROCHA, T.; B<>SCARO, H. H.; PERES, S. M.. Hand Movement Recognition for 
+	  Brazilian Sign Language: A Study Using Distance-Based Neural Networks. In: 2009 International Joint 
+	  Conference on Neural Networks, 2009, Atlanta, GA. Proceedings of 2009 International Joint Conference 
+	  on Neural Networks. Eau Claire, WI, USA : Documation LLC, 2009. p. 697-704. 
+	  Digital Object Identifier 10.1109/IJCNN.2009.5178917 
+
+
+4. Relevant Information:
+
+   --- LIBRAS, acronym of the Portuguese name "L<>ngua BRAsileira de Sinais", is the oficial brazilian sign language.
+
+   --- The dataset (movement_libras) contains 15 classes of 24 instances each, where each class references to a hand 
+       movement type in LIBRAS. The hand movement is represented as a bidimensional curve performed by the hand in a 
+       period of time. The curves were obtained from videos of hand movements, with the Libras performance from 4 
+       different people, during 2 sessions. Each video corresponds to only one hand movement and has about $7$ seconds. 
+
+   --- Each video corresponds to a function F in a functions space which is the continual version of the input dataset.
+
+   --- In the video pre-processing, a time normalization is carried out selecting 45 frames from each video, in according 
+       to an uniform distribution. In each frame, the centroid pixels of the segmented objects (the hand) are found, which 
+       compose the discrete version of the curve F with 45 points. All curves are normalized in the unitary space.
+
+   --- In order to prepare these movements to be analysed by algorithms, we have carried out a mapping operation, that is, 
+       each curve F is mapped in a representation with 90 features, with representing the coordinates of movement. 
+
+   --- Each instance represents 45 points on a bi-dimensional space, which can be plotted in an ordered way (from 1 through
+       45 as the X co-ordinate) in order to draw the path of the movement.
+
+5. Number of Instances: 360 (24 in each of fifteen classes)
+
+6. Number of Attributes: 90 numeric (double) and 1 for the class (integer)
+
+7. Attribute Information:
+   1. 1<> coordinate abcissa
+   2. 1<> coordinate ordinate
+   3. 2<> coordinate abcissa
+   4. 2<> coordinate ordinate
+   ...
+   89. 45<34> coordinate abcissa
+   90. 45<34> coordinate ordinate
+   91. class: 
+		-- 1: curved swing
+		-- 2: horizontal swing
+		-- 3: vertical swing
+		-- 4: anti-clockwise arc
+		-- 5: clockwise arc
+		-- 6: circle
+		-- 7: horizontal straight-line
+		-- 8: vertical straight-line
+		-- 9: horizontal zigzag
+		-- 10: vertical zigzag
+		-- 11: horizontal wavy
+		-- 12: vertical wavy
+		-- 13: face-up curve
+		-- 14: face-down curve 
+		-- 15: tremble
+
+8. Missing Attribute Values: None
+
+9. Class Distribution: 6.66% for each of 15 classes.
+
+10. Extra Information
+
+(a)
+	Applying a simple k-nearest neighbors algorithm (with Euclidean distance), it has been obtained the values below:
+
+--- (%) perc of instance which have been correctly placed in a same group 
+--- using the complete dataset: 24 instances per class, 15 classes
+
+				    |	mean of correct | standard deviate | max of correct / class | min of correct / class
+				    |	grouping (%)    |			     | grouping (%)		| grouping (%)
+-------------------------------------------------------------------------------------------------------------------
+      24-nearest neighbors  |	0.3918	    | 0.1267	     | 0.5556	/	5	| 0.2587	/	10
+-------------------------------------------------------------------------------------------------------------------
+neighbors in a ratio = 1.0  |	0.2245  	    |	0.0979	     | 0.3957	/	9	| 0.1181	/	 1
+-------------------------------------------------------------------------------------------------------------------
+neighbors in a ratio = 2.0  |	0.3514	    |	0.1210	     | 0.4514	/	9	| 0.2500	/	10
+-------------------------------------------------------------------------------------------------------------------
+neighbors in a ratio = 3.0  |	0.3848	    |	0.1266	     | 0.5347	/	5	| 0.2587	/	10
+-------------------------------------------------------------------------------------------------------------------
+
+
+(b) 
+	In order to support the comparisons with the experiments of the paper cited in 3(3.1) (Past Usage),
+we supply you the sub-datasets:
+
+	1. movement_libras_1.data
+	2. movement_libras_5.data
+	3. movement_libras_8.data
+	4. movement_libras_9.data
+	5. movement_libras_10.data