-0.60 * log2(0.60) - 0.40 * log2(0.40)
curve(-x * log2(x) - (1 - x) * log2(1 - x),
col = "red", xlab = "x", ylab = "Entropy", lwd = 4)
credit <- read.csv("credit.csv", stringsAsFactors = TRUE)
str(credit)
View(credit)
table(credit$checking_balance)
table(credit$savings_balance)
summary(credit$months_loan_duration)
summary(credit$amount)
table(credit$default)
set.seed(123)
train_sample <- sample(1000, 900)
str(train_sample)
credit_train <- credit[train_sample, ]
credit_test  <- credit[-train_sample, ]
prop.table(table(credit_train$default))
prop.table(table(credit_test$default))
library(C50)
credit_model <- C5.0(credit_train[-17], credit_train$default)
View(credit_train)
credit_model
summary(credit_model)
credit_pred <- predict(credit_model, credit_test)
library(gmodels)
CrossTable(credit_test$default, credit_pred,
prop.chisq = FALSE, prop.c = FALSE, prop.r = FALSE,
dnn = c('actual default', 'predicted default'))
credit_boost10 <- C5.0(credit_train[-17], credit_train$default,
trials = 10)
credit_boost10
summary(credit_boost10)
credit_boost_pred10 <- predict(credit_boost10, credit_test)
CrossTable(credit_test$default, credit_boost_pred10,
prop.chisq = FALSE, prop.c = FALSE, prop.r = FALSE,
dnn = c('actual default', 'predicted default'))
matrix_dimensions <- list(c("no", "yes"), c("no", "yes"))
names(matrix_dimensions) <- c("predicted", "actual")
matrix_dimensions
error_cost <- matrix(c(0, 1, 4, 0), nrow = 2, dimnames = matrix_dimensions)
error_cost
credit_cost <- C5.0(credit_train[-17], credit_train$default,
costs = error_cost)
credit_cost_pred <- predict(credit_cost, credit_test)
CrossTable(credit_test$default, credit_cost_pred,
prop.chisq = FALSE, prop.c = FALSE, prop.r = FALSE,
dnn = c('actual default', 'predicted default'))
credit <- read.csv("credit.csv", stringsAsFactors = TRUE)
str(credit)
View(credit)
table(credit$checking_balance)
table(credit$savings_balance)
summary(credit$months_loan_duration)
summary(credit$amount)
table(credit$default)
set.seed(123)
train_sample <- sample(1000, 900)
str(train_sample)
credit_train <- credit[train_sample, ]
credit_test  <- credit[-train_sample, ]
library(C50)
credit_model <- C5.0(credit_train[-17], credit_train$default)
credit_model
summary(credit_model)
credit_pred <- predict(credit_model, credit_test)
library(gmodels)
CrossTable(credit_test$default, credit_pred,
prop.chisq = FALSE, prop.c = FALSE, prop.r = FALSE,
dnn = c('actual default', 'predicted default'))
credit_boost10 <- C5.0(credit_train[-17], credit_train$default,
trials = 10)
credit_boost10
summary(credit_boost10)
credit_boost_pred10 <- predict(credit_boost10, credit_test)
CrossTable(credit_test$default, credit_boost_pred10,
prop.chisq = FALSE, prop.c = FALSE, prop.r = FALSE,
dnn = c('actual default', 'predicted default'))
matrix_dimensions <- list(c("no", "yes"), c("no", "yes"))
names(matrix_dimensions) <- c("predicted", "actual")
matrix_dimensions
error_cost <- matrix(c(0, 1, 4, 0), nrow = 2, dimnames = matrix_dimensions)
error_cost
credit_cost <- C5.0(credit_train[-17], credit_train$default,
costs = error_cost)
credit_cost_pred <- predict(credit_cost, credit_test)
CrossTable(credit_test$default, credit_cost_pred,
prop.chisq = FALSE, prop.c = FALSE, prop.r = FALSE,
dnn = c('actual default', 'predicted default'))
install.packages("rtoot")
library(rtoot)
auth_setup()
get_timeline_public()
get_timeline_home()
get_fedi_instances()
auth_setup()
auth_setup()
get_timeline_public()
get_timeline_home()
get_timeline_home()
get_fedi_instances()
str(get_instance_general(instance = "scholar.social"))
get_instance_activity()
get_instance_activity(scholar.social)
get_instance_activity(instance = "fosstodon.org")
get_instance_activity(instance = "scholar.social")
get_timeline_public(instance = "mastodon.social")
x <- get_timeline_public(instance = "mastodon.social")
head(x)
View(x)
get_timeline_hashtag(hashtag = "rstats", instance = "fosstodon.org")
y <- get_timeline_hashtag(hashtag = "rstats", instance = "fosstodon.org")
View(y)
get_timeline_home()
post_toot(status = "my first rtoot #rstats")
y <- get_timeline_hashtag(hashtag = "rstats", instance = "fosstodon.org", limit=40)
