Good day,
I have applied lightGBM algorithm to real estate price data set (85524 observations and 167 features). I want to receive the interaction between year and real estate area size to price. The dependent variable is transformed with log1p to get normal distribution.
I have used Python, pdpbox module to generate an interaction plot. As I understand the coloring is the average price between the variables, however, I would like to receive the interval of the interaction i.e. min and max. Is it possible to do so?
LGBMR.fit(df_train.drop(["Price"], axis = 1, inplace = False), df_train["Price"])
feats = ['Year', 'Real estate area']
p = pdp.pdp_interact(LGBMR, df, model_features = columns, features = feats)
pdp.pdp_interact_plot(p, feats, plot_type = 'grid')
I am adding the pdp interaction plot. For example, in 2008 year, the real estate object of size 0.52 was purchased for an average price of 5.697 (prediction), but I would like to know the min and max predicted price of this interaction.
