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Acturio-predictions2.R
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#### Librerias ####
library(readr)
library(tidyr)
library(DataExplorer)
library(dplyr)
library(purrr)
library(stringr)
library(tidymodels)
library(tidypredict)
#### LECTURA DE ARCHIVOS ####
casas <- read_csv("data/casas_entrena.csv")
casas_prueba <- read_csv("data/casas_prueba.csv")
#### TRATAMIENTO ####
names(casas) <- names(casas) %>% map_chr(str_replace_all," ", "_" )
casas <- casas %>%
mutate(Pool_QC = replace_na(Pool_QC, 0),
Alley= replace_na(Alley, "Missing"),
Fence= replace_na(Fence, "Missing"),
Fireplace_Qu= replace_na(Fireplace_Qu, "Missing"),
Lot_Frontage=replace_na(Lot_Frontage, 0),
Garage_Yr_Blt = if_else(is.na(Garage_Yr_Blt), Year_Built, Garage_Yr_Blt),
Garage_Type = replace_na (Garage_Type, "Missing"),
Garage_Finish = replace_na( Garage_Finish,"Missing"),
Garage_Qual = replace_na(Garage_Qual, "Missing"),
Garage_Cond =replace_na(Garage_Cond, "Missing"),
Bsmt_Qual =replace_na(Bsmt_Qual, "Missing"),
Bsmt_Cond = replace_na(Bsmt_Cond, "Missing"),
Bsmt_Exposure =replace_na(Bsmt_Exposure, "Missing"),
BsmtFin_Type_1 =replace_na(BsmtFin_Type_1, "Missing"),
BsmtFin_Type_2 =replace_na(BsmtFin_Type_2, "Missing"),
Mas_Vnr_Type =replace_na(Mas_Vnr_Type, "Missing"),
Mas_Vnr_Area = replace_na(Mas_Vnr_Area, 0),
Bsmt_Full_Bath = replace_na(Bsmt_Full_Bath, 0),
Bsmt_Half_Bath = replace_na(Bsmt_Half_Bath, 0),
Electrical = replace_na(Electrical, "Missing") ,
Heating_QC = replace_na(Heating_QC, "Missing"),
SalePrice_m2 = SalePrice/Gr_Liv_Area,
ID = 1:nrow(casas)) %>% filter (Sale_Condition == 'Normal') %>%
mutate_if(is.character, as.factor)
names(casas_prueba) <- names(casas_prueba) %>% map_chr(str_replace_all," ", "_" )
casas_prueba <- casas_prueba %>%
mutate(Pool_QC = replace_na(Pool_QC, 0),
Alley= replace_na(Alley, "Missing"),
Fence= replace_na(Fence, "Missing"),
Fireplace_Qu= replace_na(Fireplace_Qu, "Missing"),
Lot_Frontage=replace_na(Lot_Frontage, 0),
Garage_Yr_Blt = if_else(is.na(Garage_Yr_Blt), Year_Built, Garage_Yr_Blt),
Garage_Type = replace_na (Garage_Type, "Missing"),
Garage_Finish = replace_na( Garage_Finish,"Missing"),
Garage_Qual = replace_na(Garage_Qual, "Missing"),
Garage_Cond =replace_na(Garage_Cond, "Missing"),
Bsmt_Qual =replace_na(Bsmt_Qual, "Missing"),
Bsmt_Cond = replace_na(Bsmt_Cond, "Missing"),
Bsmt_Exposure =replace_na(Bsmt_Exposure, "Missing"),
BsmtFin_Type_1 =replace_na(BsmtFin_Type_1, "Missing"),
BsmtFin_Type_2 =replace_na(BsmtFin_Type_2, "Missing"),
Mas_Vnr_Type =replace_na(Mas_Vnr_Type, "Missing"),
Mas_Vnr_Area = replace_na(Mas_Vnr_Area, 0),
Bsmt_Full_Bath = replace_na(Bsmt_Full_Bath, 0),
Bsmt_Half_Bath = replace_na(Bsmt_Half_Bath, 0),
Electrical = replace_na(Electrical, "Missing"),
Heating_QC = replace_na(Heating_QC, "Missing")
) %>%
mutate_if(is.character, as.factor)
#### Variables ####
casas_df1 = casas %>%
dplyr::filter (Sale_Condition == 'Normal') %>%
dplyr::select (SalePrice_m2,
Overall_Qual,
Year_Built ,
Year_Remod = 'Year_Remod/Add',
Mas_Vnr_Area ,
Total_Bsmt_SF ,
First_Flr_SF = '1st_Flr_SF',
Second_Flr_SF = '2nd_Flr_SF',
Gr_Liv_Area ,
Full_Bath,
Half_Bath,
Bsmt_Full_Bath,
Bsmt_Half_Bath,
TotRms_AbvGrd ,
Garage_Yr_Blt ,
Garage_Cars ,
Garage_Area,
Exter_Qual,
#Foundation,
Kitchen_Qual,
Kitchen_AbvGr,
Fireplaces,
Fireplace_Qu,
Yr_Sold,
Enclosed_Porch,
ThirdSsn_Porch = "3Ssn_Porch",
Screen_Porch,
Open_Porch_SF,
Bldg_Type,
MS_Zoning,
Lot_Frontage,
Lot_Shape,
Land_Contour,
Lot_Config,
Land_Slope,
Condition_1,
Overall_Cond,
Exter_Cond,
Bsmt_Qual,
Bsmt_Cond,
BsmtFin_Type_1,
BsmtFin_SF_1,
BsmtFin_Type_2,
Bsmt_Exposure,
Heating_QC,
Central_Air,
Bedroom_AbvGr,
Misc_Val, # Revisar colapsar
Neighborhood,
Exter_Qual,
Functional,
Pool_Area,
ID
)
##### Plots #####
casas %>% ggplot(aes(x = reorder(Neighborhood, SalePrice_m2, median), y = SalePrice_m2)) +
geom_boxplot() +
geom_jitter()
##### Partición #####
set.seed(20180911)
casas_split <- initial_split(casas_df1, prop = .7)
casas_train <- training(casas_split)
casas_test <- testing(casas_split)
### Receta #####
casas_rec <- recipe(SalePrice_m2 ~ . , data = casas_train) %>%
update_role(ID, new_role = "id variable") %>%
#step_filter(!ID %in% c(419, 404, 855, 427, 294, 249, 872, 311, 58, 272, 951, #
# 899, 981, 858, 324, 1159, 853, 213, 428)) %>%
step_filter(!ID %in% c(480, 386, 300, 500, 1229, 349, 1169, 320, 70)) %>%
step_mutate(#TotalBaths = Full_Bath + Bsmt_Full_Bath + 0.5 * (Half_Bath + Bsmt_Half_Bath),
Garage_Yr_Blt = if_else(is.na(Garage_Yr_Blt), Year_Built, Garage_Yr_Blt),
Age_House = Yr_Sold - Year_Remod,
TotalSF = Gr_Liv_Area + Total_Bsmt_SF,
Overall_Qual_2 = Overall_Qual^2,
Overall_Qual_3 = Overall_Qual^3,
#AvgRoomSF = Gr_Liv_Area / TotRms_AbvGrd,
Porch_SF = Enclosed_Porch + ThirdSsn_Porch + Open_Porch_SF,
Porch = factor(Porch_SF > 0),
Pool = if_else(Pool_Area > 0,1,0),
# anio_mes = lubridate::make_date(year = as.numeric(Yr_Sold),
# month = as.numeric(Mo_Sold)) %>%
# as.factor()
) %>%
#step_interact(~ Overall_Qual:TotalBaths) %>%
step_interact(~ Overall_Cond:TotRms_AbvGrd) %>%
step_interact(~ Overall_Qual:TotRms_AbvGrd) %>%
step_interact(~ Overall_Qual:Gr_Liv_Area) %>%
#step_interact(~ Overall_Qual:Overall_Cond) %>%
#step_interact(~ Overall_Cond:Age_House) %>%
step_interact(~ Overall_Qual:Total_Bsmt_SF) %>%
#step_interact(~ Overall_Cond:Garage_Area) %>%
step_interact(~ TotalSF:Age_House) %>%
step_interact(~ Second_Flr_SF:Bedroom_AbvGr) %>%
step_interact(~ TotalSF:TotRms_AbvGrd) %>%
#step_interact(~ Age_House:TotRms_AbvGrd) %>%
#step_interact(~ Overall_Qual:Misc_Val) %>%
step_interact(~ Overall_Cond:Bedroom_AbvGr) %>%
#step_interact(~ Second_Flr_SF:First_Flr_SF) %>%
step_interact(~ Year_Built:Garage_Yr_Blt) %>%
step_ratio(Bedroom_AbvGr, denom = denom_vars(Gr_Liv_Area)) %>%
step_ratio(Second_Flr_SF, denom = denom_vars(First_Flr_SF)) %>%
step_mutate(Exter_Cond = fct_collapse(Exter_Cond, Bad = c("Po", "Fa"),
TA = c("TA", "Gd", "Ex")),
Condition_1 = fct_collapse(Condition_1,
Artery_Feedr = c("Feedr", "Artery"), # Revisar
Railr = c("RRAn", "RRNn", "RRNe", "RRAe"),
Norm = "Norm",
Pos = c("PosN", "PosA")), #cambioV
Land_Slope = fct_collapse(Land_Slope, Mod_Sev = c("Mod", "Sev")),
Land_Contour = fct_collapse(Land_Contour, Low_HLS = c("Low","HLS"),
Bnk_Lvl = c("Lvl","Bnk")),
Lot_Shape = fct_collapse(Lot_Shape, IRREG = c("IR3", "IR2", "IR1")),
Kitchen_Qual = fct_collapse(Kitchen_Qual, Bad = c("Fa", "Po")),
Bsmt_Cond = fct_collapse(Bsmt_Cond, Exc = c("Gd", "Ex"),
Bad = c("Po", "Missing")),
#Bsmt_Qual = fct_collapse(Bsmt_Qual, Fa_Po = c("Fa", "Po")),
BsmtFin_Type_1 = fct_collapse(BsmtFin_Type_1, Rec_BLQ = c("Rec", "BLQ")),
BsmtFin_Type_2 = fct_collapse(BsmtFin_Type_2, Rec_BLQ = c("Rec", "BLQ", "LwQ")),
Neighborhood = fct_collapse(Neighborhood, Greens_GrnHill = c("Greens", "GrnHill"),#
Blueste_Veenker = c("Blueste", "Veenker"),#
Blmngtn_Timber = c("Blmngtn", "Timber"),#
NPkVill_NAmes = c("NPkVill", "NAmes"),#
ClearCr_NridgHt_StoneBr = c("ClearCr","NridgHt", "StoneBr"),#
BrDale_OldTown = c("BrDale", "OldTown"), #
SWISU_Sawyer = c("SWISU", "MeadowV, IDOTRR")#
),
Fireplace_Qu = fct_collapse(Fireplace_Qu, Miss = c("Po", "Missing")),
#Heating_QC = fct_collapse(Heating_QC, Miss = c("Po", "OthW")),
MS_Zoning = fct_collapse(MS_Zoning, I_R_M_H = c("RM", "I (all)", "RH", "A (agr)")),
#Bldg_Type = fct_collapse(Bldg_Type, Du_Tu = c("Duplex", "Twnhs")),
#Foundation = fct_collapse(Foundation, Wood_Stone = c("Wood", "Stone")),
#Functional = fct_collapse(Functional, Min = c("Min1", "Min2"), Maj = c("Maj1", "Maj2", "Mod"))
) %>%
step_relevel(Bsmt_Qual, ref_level = "TA") %>%
step_relevel(Condition_1, ref_level = "Norm") %>%
step_normalize(all_predictors(), -all_nominal()) %>%
step_dummy(all_nominal()) %>%
#step_interact(~ matches("Bsmt_Qual"):Total_Bsmt_SF) %>%
step_interact(~ matches("Bsmt_Qual"):TotRms_AbvGrd) %>%
#step_interact(~ matches("Bsmt_Qual"):Bedroom_AbvGr) %>%
#step_interact(~ matches("Bsmt_Cond"):TotRms_AbvGrd) %>%
step_interact(~ matches("BsmtFin_Type_1"):BsmtFin_SF_1) %>%
#step_interact(~ matches("BsmtFin_Type_1"):Total_Bsmt_SF) %>%
step_interact(~ matches("Kitchen_Qual"):Kitchen_AbvGr) %>%
step_interact(~ matches("Heating_QC"):TotRms_AbvGrd) %>%
step_interact(~ matches("Heating_QC"):TotalSF) %>%
step_interact(~ matches("Heating_QC"):Second_Flr_SF) %>%
#step_interact(~ matches("Neighborhood"):matches("Condition_1")) %>%
step_rm(First_Flr_SF, Second_Flr_SF, Year_Remod, Yr_Sold,
Bsmt_Full_Bath, Bsmt_Half_Bath,
Kitchen_AbvGr, BsmtFin_Type_1_Unf,
Total_Bsmt_SF, Kitchen_AbvGr, Overall_Qual, Pool_Area, ID,
#Bsmt_Qual_Gd_x_Total_Bsmt_SF_x_TotRms_AbvGrd,
Heating_QC_TA_x_TotRms_AbvGrd_x_TotalSF_x_Second_Flr_SF,
#Bsmt_Qual_Fa_x_Total_Bsmt_SF_x_Bedroom_AbvGr,
Gr_Liv_Area, Bsmt_Qual_Missing,
#Bsmt_Qual_Missing_x_Total_Bsmt_SF,
Bsmt_Qual_Missing_x_TotRms_AbvGrd,
#Bsmt_Qual_Missing_x_Bedroom_AbvGr,
#Bsmt_Qual_Missing_x_TotRms_AbvGrd_x_Bedroom_AbvGr,
BsmtFin_Type_1_Missing,
BsmtFin_Type_2_Missing,
BsmtFin_Type_1_Missing_x_BsmtFin_SF_1,
Porch_SF,
#BsmtFin_Type_1_Missing_x_BsmtFin_SF_1_x_Total_Bsmt_SF,
#BsmtFin_Type_1_Unf_x_BsmtFin_SF_1_x_Total_Bsmt_SF,
Kitchen_Qual_Gd_x_Kitchen_AbvGr,
Bsmt_Cond_Fa, Bsmt_Cond_TA,Bsmt_Qual_Po,
Heating_QC_Fa_x_TotRms_AbvGrd_x_Second_Flr_SF,
Heating_QC_Fa_x_TotalSF,
Heating_QC_Fa_x_TotalSF_x_Second_Flr_SF,
Bsmt_Qual_Po_x_TotRms_AbvGrd
) %>%
prep()
### Ajuste de Receta
casa_juiced <- juice(casas_rec)
### Modelo 1 ###
modelo1 <- linear_reg() %>%
set_mode("regression") %>%
set_engine("lm")
lm_fit1 <- fit(modelo1, SalePrice_m2 ~ ., casa_juiced)
p_test <- predict(lm_fit1, bake(casas_rec, casas_test)) %>%
bind_cols(casas_test) %>%
dplyr::mutate(.pred = .pred * Gr_Liv_Area,
SalePrice = SalePrice_m2* Gr_Liv_Area) %>%
dplyr::mutate(err = (log(1 + SalePrice) - log(1 + .pred))^2)
p_test %>% pull(err) %>% mean() %>% sqrt() # 0.08656526
p_test %>%
arrange(desc(err)) %>%
as.data.frame() %>% head(10)
lm_fit1 %>% tidy() %>% arrange(desc(p.value)) %>%
as.data.frame() %>% head(30)
p_test %>% ggplot(aes(x= SalePrice, y=.pred)) + geom_point()
########
#######
#######
#### PRUEBA KAGGLE####
casas_prueba[696, "Heating_QC"] <- "Fa"
test <- casas_prueba %>%
dplyr::filter (Sale_Condition == 'Normal') %>%
dplyr::select (Overall_Qual,
Year_Built ,
Year_Remod = 'Year_Remod/Add',
Mas_Vnr_Area ,
Total_Bsmt_SF ,
First_Flr_SF = '1st_Flr_SF',
Second_Flr_SF = '2nd_Flr_SF',
Gr_Liv_Area ,
Full_Bath,
Half_Bath,
Bsmt_Full_Bath,
Bsmt_Half_Bath,
TotRms_AbvGrd ,
Garage_Yr_Blt ,
Garage_Cars ,
Garage_Area,
Exter_Qual,
#Foundation,
Kitchen_Qual,
Kitchen_AbvGr,
Fireplaces,
Fireplace_Qu,
Yr_Sold,
Enclosed_Porch,
ThirdSsn_Porch = "3Ssn_Porch",
Screen_Porch,
Open_Porch_SF,
Bldg_Type,
MS_Zoning,
Lot_Frontage,
Lot_Shape,
Land_Contour,
Lot_Config,
Land_Slope,
Condition_1,
Overall_Cond,
Exter_Cond,
Bsmt_Qual,
Bsmt_Cond,
BsmtFin_Type_1,
BsmtFin_SF_1,
BsmtFin_Type_2,
Bsmt_Exposure,
Heating_QC,
Central_Air,
Bedroom_AbvGr,
Misc_Val, # Revisar colapsar
Neighborhood,
Exter_Qual,
Functional,
Pool_Area
)
train <- casas_df1
casas_rec_KAGGLE <- casas_rec
casa_juiced_KAGGLE <- juice(casas_rec_KAGGLE)
lm_fit1_KAGGLE <- fit(modelo1, SalePrice_m2 ~ ., casa_juiced_KAGGLE)
lm_fit1_KAGGLE
submission1 <- predict(lm_fit1_KAGGLE, bake(casas_rec_KAGGLE, test)) %>%
bind_cols(test) %>% mutate(SalePrice=.pred*Gr_Liv_Area)
submission1_KAGGLE <- submission1 %>%
mutate(id=row.names(submission1)) %>%
select(id, SalePrice)
submission1_KAGGLE[is.na(submission1_KAGGLE$SalePrice),]
write_csv(submission1_KAGGLE, "Acturio_sub2.csv")
### Modelo 2 ###
modelo_RF <- rand_forest(mtry = 30, trees = 3000, min_n = 10) %>%
set_engine("ranger", importance = "impurity_corrected", verbose = T) %>%
set_mode("regression") %>% translate()
rf_fit1 <- fit(modelo_RF, SalePrice_m2 ~ ., casa_juiced)
rf_fit1
tibble(variable = reorder(names(rf_fit1$fit$variable.importance),
rf_fit1$fit$variable.importance),
value = rf_fit1$fit$variable.importance) %>%
arrange(desc(value)) %>% head(100) %>%
ggplot(aes(x = variable, y = value)) +
geom_bar(fill = "blue", stat = "identity") +
theme(text = element_text(size = 8)) +
coord_flip()
p_test_rf <- predict(rf_fit1, bake(casas_rec, casas_test)) %>%
bind_cols(., casas_test) %>%
mutate(.pred=.pred*Gr_Liv_Area, SalePrice = SalePrice_m2*Gr_Liv_Area) %>%
mutate(err = (log(1+SalePrice) - log(1 + .pred))^2)
p_test_rf$err %>% mean() %>% sqrt()