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plot = pdp.PDPIsolate(model=model,df=tree_temp,model_features=X.columns ,feature='UrbanCPI',feature_name='UrbanCPI',n_classes=0,num_grid_points=10) fig, axes= plot.plot( ncols=2, engine='plotly', template='plotly_white', center=False,# True为纵坐标显示原目标值-均值后的结果 frac_to_plot=100, plot_params={ "pdp_hl": True ,"title": {"title": {"text": ''},"subtitle": {"text": ''},} ,"xlabel":45 }, plot_pts_dist=True, to_bins=True, )
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Check this example: https://github.com/SauceCat/PDPbox/blob/master/tutorials/pdpbox_binary_classification.ipynb You can achieve this through fig.update_layout if you use plotly as the plot engine, otherwise you can do sth like this: _ = axes['bar_axes'][0].set_xticklabels(['Female', 'Male']) for matplotlib axes
fig.update_layout
plotly
_ = axes['bar_axes'][0].set_xticklabels(['Female', 'Male'])
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The text was updated successfully, but these errors were encountered: