:ia FSSKJr SSKrSSKJr SSKJr SSKJ r SSjr g) N) convert_name)colors)labelsc Uc;[URS5Vs/sHn[S[U5-PM nn[ XU5nUS:XaUR S5nSnO USS2U4nX n[ U[5(a7US:Xa1[RRS5n U RU5n O3[US5(aURSS:XaUn O [S U5 [R"W SS2S 4U SS2S4U[R US S 9 [R""S 5 [R$"5n U R'S U-SS9 U R(R+S5 [R,"5R/SS5 U R0R35R5[R,"5R6R955n U R0R;U R<S- S-5 U R?S5 U(a[R@"5 ggs snf)aPUse the SHAP values as an embedding which we project to 2D for visualization. Parameters ---------- ind : int or string If this is an int it is the index of the feature to use to color the embedding. If this is a string it is either the name of the feature, or it can have the form "rank(int)" to specify the feature with that rank (ordered by mean absolute SHAP value over all the samples), or "sum()" to mean the sum of all the SHAP values, which is the model's output (minus it's expected value). shap_values : numpy.array Matrix of SHAP values (# samples x # features). feature_names : None or list The names of the features in the shap_values array. method : "pca" or numpy.array How to reduce the dimensions of the shap_values to 2D. If "pca" then the 2D PCA projection of shap_values is used. If a numpy array then is should be (# samples x 2) and represent the embedding of that values. alpha : float The transparency of the data points (between 0 and 1). This can be useful to the show density of the data points when using a large dataset. NrFEATUREzsum()zsum(SHAP values)pcarshapezUnsupported embedding method:r)ccmapalpha linewidthoffzSHAP value for )sizeFg@gffffff? )!ranger rstrrsum isinstancesklearn decompositionPCA fit_transformhasattrprintpltscatterrred_blueaxiscolorbar set_labeloutline set_visiblegcfset_size_inchesaxget_window_extent transformeddpi_scale_transinverted set_aspectheight set_alphashow) ind shap_values feature_namesmethodrr1icvalsfnamer embedding_valuescbbboxs X/srv/projetos/modelo_ml_acdoc/venv/lib/python3.13/site-packages/shap/plots/_embedding.py embeddingr= s8=B;CTCTUVCW=XY=X *SV3=X Y s 7C g~""AsF#"&#6U?##''*,,[9  ! !fll1o&:! -v6KK A&(8A(>%fooejvwxHHUO BLL#e+"L5JJ5!GGIc1% 55 " " $ 0 01J1J1S1S1U VDEEdkkC'2-.LLO    =ZsI)Nr g?T) matplotlib.pyplotpyplotrrutilsrr_labelsrr=r<rEs <rD