Edytuj stronę Odnośniki Fold/unfold all ODT export Ta strona jest tylko do odczytu. Możesz wyświetlić źródła tej strony ale nie możesz ich zmienić. ====== QPC+NaiveBayes CV test on 10 first projections for Sonar ====== Test klasyfikacji 10x10CV dla modelu Naive Bayes (przy założeniu rozkładu normalnego, default Matlab settings) uczonego na całym zbiorze Sonar oraz na pierwszych 10 kierunkach znalezionych przez QPC maksymalizowanego za pomocą spadku gradientu oraz za pomocą zmodyfikowanej wersji QPC bazującej na zbiorze prototypów referencyjnych i inicjowanej za pomocą podziału losowych projekcji na interwały. ~~META: description abstract = Naive Bayes classiffication 10x10 crossvalidation test on 10 first QPC projections ~~ ===== 10x10 CV, 10 first projections (10.05.15) ===== 10x10 CV normalization QPC parameters lr = 0.1 optimization = gradient descent dataset= sonar vectors= 208 features= 60 folds= 10 repetitions=10 ttest paired corrected ^ Naive Bayes (all data) ^^ | acc. | std. | | 67.95 | 11.28 | <sortable 1> ^ Dim. ^ QPC ^^ T-Test vs. NB ^ QPC2 ^^ T-Test vs. NB ^ T-Test vs. QPC ^ | | acc. | std. | p-value | acc. | std. | p-value | p-value | | 1 | **74.41** | 9.44 | 0.0819 | **74.23** | 8.45 | 0.0700 | 0.9290 | | 2 | **75.19** | 8.68 | 0.0482 | **74.60** | 9.52 | 0.0621 | 0.8029 | | 3 | **76.68** | 9.11 | 0.0195 | **74.56** | 9.08 | 0.0683 | 0.3609 | | 4 | **76.61** | 8.33 | 0.0182 | **76.39** | 9.16 | 0.0213 | 0.9255 | | 5 | **76.87** | 8.05 | 0.0195 | **76.73** | 8.61 | 0.0145 | 0.9479 | | 6 | **77.50** | 7.32 | 0.0114 | **78.31** | 8.41 | 0.0041 | 0.7347 | | 7 | **77.49** | 7.52 | 0.0112 | **78.62** | 7.80 | 0.0025 | 0.6373 | | 8 | **78.69** | 7.17 | 0.0039 | **79.19** | 8.38 | 0.0020 | 0.8445 | | 9 | **78.55** | 7.32 | 0.0039 | **78.86** | 8.78 | 0.0037 | 0.9017 | | 10 | **78.56** | 7.66 | 0.0039 | **79.09** | 9.17 | 0.0022 | 0.8328 | </sortable> Dim. - number of linear ptojections generated by QPC \\ QPC2 - fast QPC method based on subset of reference prototypes\\ NB - Naive Bayes with normal distribution assumption\\ {{:projects:models:qpc_and_naivebayes:sonar_10x10_dim_1_10.png|{{:projects:models:qpc_and_naivebayes:sonar_10x10_dim_1_10.png|}} ===== 1x10 CV , 10 first projections (10.05.14) ===== 1x10 CV normalization QPC parameters lr = 0.1 optimization = gradient descent ^ NaiveBayes ^^ | acc. | std. | | **70.64** | 13.80 | ^ Dim. ^ QPC + NB ^^ QPC2 + NB ^^ | | acc. | std. | acc. | std. | | 1 | **74.02** | 14.25 | **73.02** | 10.55 | | 2 | **74.52** | 13.29 | **74.97** | 10.29 | | 3 | **76.02** | 13.93 | **76.95** | 12.21 | | 4 | **77.90** | 12.51 | **78.85** | 10.32 | | 5 | **77.42** | 12.65 | **79.83** | 10.18 | | 6 | **76.47** | 12.72 | **77.90** | 11.68 | | 7 | **76.95** | 12.79 | **77.45** | 11.81 | | 8 | **76.95** | 11.77 | **78.88** | 10.75 | | 9 | **78.38** | 11.91 | **78.40** | 11.21 | | 10 | **79.33** | 12.30 | **78.90** | 11.40 | Dim. - number of linear ptojections generated by QPC \\ QPC2 - fast QPC method based on subset of reference prototypes\\ NB - Naive Bayes with normal distribution assumption\\ {{:projects:models:qpc_and_naivebayes:sonar_1-100.png|}}