library(dplyr)
ames_subset <- modeldata::ames |>
dplyr::select(
Sale_Price,
MS_SubClass,
MS_Zoning,
Lot_Frontage,
Lot_Area,
Street
)
ames_subset <- ames_subset |>
dplyr::mutate(Sale_Price = log10(Sale_Price))
# ANOVA p-value
ames_aov_pval_res <-
score_aov_pval |>
fit(Sale_Price ~ ., data = ames_subset)
ames_aov_pval_res@results
# Pearson correlation
ames_cor_pearson_res <-
score_cor_pearson |>
fit(Sale_Price ~ ., data = ames_subset)
ames_cor_pearson_res@results
# Create a list
class_score_list <- list(
ames_aov_pval_res,
ames_cor_pearson_res
)
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