include mapping

pipeline/02-assess.R

@@ -41,19 +41,31 @@ lgbm_final_full_recipe <- readRDS(paths$output$workflow_recipe$local)
 # Load the data for assessment. This is the universe of condo units
 # that need values. Use the trained lightgbm model to estimate a single
 # FMV per unit
-tic()
 assessment_data_pred <- read_parquet(paths$input$assessment$local) %>%
   as_tibble() %>%
-  # Bake the recipe once and store the result in a variable
-  { baked_data <- bake(lgbm_final_full_recipe, new_data = .);
+  # Bake the data first and extract meta strata columns
+  { baked_data <- bake(lgbm_final_full_recipe, new_data = ., all_predictors());
   mutate(
     .,
-    pred_card_initial_fmv = predict(lgbm_final_full_fit, new_data = baked_data)$.pred,
+    pred_card_initial_fmv = as.numeric(predict(lgbm_final_full_fit, new_data = baked_data)$.pred),
     new_strata_1 = baked_data$meta_strata_1,
     new_strata_2 = baked_data$meta_strata_2
   )
   }
 
+mapping_1 <- assessment_data_pred %>%
+  select(new_strata_1, meta_strata_1) %>%
+  distinct() %>%
+  filter(!is.na(meta_strata_1)) %>%
+  arrange(new_strata_1)
+
+mapping_2 <- assessment_data_pred %>%
+  select(new_strata_2, meta_strata_2) %>%
+  distinct() %>%
+  filter(!is.na(meta_strata_2)) %>%
+  arrange(new_strata_2)
+
+
 # The imputing stage does not change any existing values. However, for the lightgbm
 # model, values have to be encoded to a base of 0. Because of this, the output does
 # not match the input. Since these are 1:1 matches, we map the new column to the old.
@@ -64,16 +76,14 @@ strata_mapping_2 <- setNames(mapping_2$meta_strata_2, mapping_2$new_strata_2)
 assessment_data_pred <- assessment_data_pred %>%
   mutate(
     # Binary variable to identify condos which have imputed strata
-    meta_strata_imputed = ifelse(is.na(meta_strata_1), 1, 0),
+    meta_strata_is_imputed = ifelse(is.na(meta_strata_1), 1, 0),
     # Use mappings to replace meta_strata_1 and meta_strata_2 directly
     meta_strata_1 = strata_mapping_1[as.character(new_strata_1)],
     meta_strata_2 = strata_mapping_2[as.character(new_strata_2)]
   ) %>%
   select(-c("new_strata_1", "new_strata_2"))
 toc()
 
-
-
 #- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
 # 3. Post-Modeling Adjustments -------------------------------------------------
 #- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
@@ -171,8 +181,8 @@ assessment_data_merged %>%
   select(
     meta_year, meta_pin, meta_class, meta_card_num, meta_lline_num,
     meta_modeling_group, ends_with("_num_sale"), pred_card_initial_fmv,
-    all_of(params$model$predictor$all), township_code, meta_strata_1, meta_strata_2,
-    meta_strata_is_imputed
+    all_of(params$model$predictor$all),
+    meta_strata_is_imputed, township_code
   ) %>%
   mutate(
     ccao_n_years_exe_homeowner = as.integer(ccao_n_years_exe_homeowner)