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scat_pca = axs [0 ].scatter (T_pca [:, 0 ], T_pca [:, 1 ], c = y )
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scat_pcovc = axs [1 ].scatter (T_pcovc [:, 0 ], T_pcovc [:, 1 ], c = y )
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fig .colorbar (scat_pca , ax = axs , orientation = "horizontal" )
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+ fig .suptitle ("Multiclass PCovC with One Label" )
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# %%
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# Next, let's try a two-label classification problem, with both labels
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handles , _ = scat_pca .legend_elements ()
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labels = labels_list [i ]
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axs [0 , i ].legend (handles , labels )
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- print (labels )
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- print (i )
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- print (handles )
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-
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-
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+
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axs [0 , 0 ].set_title ("Even/Odd" )
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axs [0 , 1 ].set_title ("Greater/Less than 5" )
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axs [0 , 2 ].set_title ("Digit" )
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axs [0 , 0 ].set_ylabel ("PCA" )
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axs [1 , 0 ].set_ylabel ("PCovC" )
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fig .colorbar (scat_pca , ax = axs , orientation = "horizontal" )
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+ fig .suptitle ("Multilabel PCovC with Binary Labels" )
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# %%
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# Let's try a more complicated example:
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handles , _ = scat_pca .legend_elements ()
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labels = labels_list [i ]
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axs [0 , i ].legend (handles , labels )
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- print (labels )
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- print (i )
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- print (handles )
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-
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axs [0 , 0 ].set_title ("Even/Odd" )
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axs [0 , 1 ].set_title ("Number of Holes" )
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axs [0 , 0 ].set_ylabel ("PCA" )
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axs [1 , 0 ].set_ylabel ("PCovC" )
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fig .colorbar (scat_pca , ax = axs , orientation = "horizontal" )
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+ fig .suptitle ("Multiclass-Multilabel PCovC" )
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