competitors-frost

Contrastación con competidores

# archivos resultado bnReg y rf por cada estacion
# nombre variable predictora

Primero correr el script util-competitors-calc.R que genera el archivo competitors-table.csv

Tabla resultados

## Registered S3 method overwritten by 'rvest':
##   method            from
##   read_xml.response xml2

## 
## Attaching package: 'kableExtra'

## The following object is masked from 'package:dplyr':
## 
##     group_rows

Station	Method	MAE	r2	RMSE	Recall	Spec	F1
junin	buildMdz	17.06	0.72	17.45	0.00	1.00	NA
junin	FAO	1.78	0.90	2.23	0.61	0.98	0.7049608
junin	RF	0.84	0.97	1.12	0.77	0.99	0.8423645
junin	BN	1.61	0.91	2.06	0.58	0.98	0.6880000
tunuyan	buildMdz	23.48	0.63	24.00	0.00	1.00	NA
tunuyan	FAO	2.35	0.84	2.90	0.79	0.95	0.8331745
tunuyan	RF	2.09	0.87	2.66	0.78	0.95	0.8213945
tunuyan	BN	2.15	0.86	2.76	0.74	0.96	0.8091451
agua_amarga	buildMdz	16.05	0.72	16.47	0.01	1.00	0.0155642
agua_amarga	FAO	1.79	0.89	2.15	0.59	0.97	0.6772009
agua_amarga	RF	1.60	0.90	2.05	0.59	0.98	0.6894977
agua_amarga	BN	1.58	0.90	2.07	0.62	0.97	0.6854664
las_paredes	buildMdz	14.78	0.72	15.27	0.00	1.00	NA
las_paredes	FAO	2.06	0.86	2.60	0.66	0.97	0.7322971
las_paredes	RF	2.10	0.84	2.79	0.53	0.98	0.6653696
las_paredes	BN	2.09	0.84	2.76	0.61	0.97	0.6939502
la_llave	buildMdz	16.85	0.71	17.35	0.00	1.00	NA
la_llave	FAO	2.38	0.85	2.94	0.74	0.96	0.7880435
la_llave	RF	2.29	0.85	2.94	0.65	0.96	0.7226174
la_llave	BN	2.23	0.85	2.94	0.72	0.95	0.7543624

Gráficos

library(ggplot2)

ggplot(data,aes(y = MAE , x = Method, fill = Station)) + geom_col()

data %>%
  filter(Method != "buildMdz") %>%
  ggplot(aes(y = MAE , x = Method, fill = Station)) + geom_col()

MAE

data %>%
  filter(Method != "buildMdz") %>%
  ggplot(aes(y = MAE , x = Station, fill = Method)) + geom_bar(stat = "identity",position=position_dodge())

RMSE

data %>%
  filter(Method != "buildMdz") %>%
  ggplot(aes(y = RMSE , x = Station, fill = Method)) + geom_bar(stat = "identity",position=position_dodge())

r2

data %>%
  filter(Method != "buildMdz") %>%
  ggplot(aes(y = r2 , x = Station, fill = Method)) + geom_bar(stat = "identity",position=position_dodge())

Recall

data %>%
  filter(Method != "buildMdz") %>%
  ggplot(aes(y = Recall , x = Station, fill = Method)) + geom_bar(stat = "identity",position=position_dodge())

## Spec

data %>%
  filter(Method != "buildMdz") %>%
  ggplot(aes(y = Spec , x = Station, fill = Method)) + geom_bar(stat = "identity",position=position_dodge())

F1

data %>%
  filter(Method != "buildMdz") %>%
  ggplot(aes(y = F1 , x = Station, fill = Method)) + geom_bar(stat = "identity",position=position_dodge())