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Tagged: Perkenalan Machine Learning
- This topic has 2 replies, 2 voices, and was last updated 3 years, 3 months ago by Coach William.
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August 4, 2023 at 4:47 PM #203885
halo coach, saya sudah mengerjakan semua kode yg coach berikan di video, tapi ada hasil error berupa
ini code yg salah tulis
df = read.csv(‘Social_Network_Ads.csv’)
df$User.ID = NULL
#FEATURE SCALING
library(caTools)
set.seed(123)split = sample.split(df$Purchased,SplitRatio = 0.7)
training_set = subset(df,split == TRUE)
test_set = subset(df,split == FALSE)#train random forest
library(randomForest)
classifier = randomForest(x = training_set[-3],
y = training_set$Purchased,#y adalah data target
ntree = 10
)classifier
# … Kode sebelumnya …
# Memperbaiki kesalahan objek ‘tes_set’ not found
y_pred = predict(classifier, newdata = test_set[-3])result = cbind(test_set, y_pred)
dan ini warningnya
Warning message:
In randomForest.default(x = training_set[-3], y = training_set$Purchased, :
The response has five or fewer unique values. Are you sure you want to do regression?ini ada di console. Jadi saya harus gimana ya coach
August 4, 2023 at 4:58 PM #203887Halo coach, maaf sekali ini biar nyambung, saya mau kasih tau kalau saya coba tanya ke chat gpt. dan setelah dibenarkan ternata untuk kolom purchased variablenya butuh di factorkan, dan hasilnya jadi ga ada error lagi coach
library(randomForest)
library(caTools)# Load the dataset
df <- read.csv(‘Social_Network_Ads.csv’)
df$User.ID <- NULL# Convert ‘Purchased’ to a factor
df$Purchased <- as.factor(df$Purchased)# Split the data
set.seed(123)
split <- sample.split(df$Purchased, SplitRatio = 0.7)
training_set <- subset(df, split == TRUE)
test_set <- subset(df, split == FALSE)# Train random forest for classification
classifier <- randomForest(x = training_set[-3],
y = training_set$Purchased,
ntree = 100,
type = “classification”)classifier
# … Kode sebelumnya …
# Memperbaiki kesalahan objek ‘tes_set’ not found
y_pred = predict(classifier, newdata = test_set[-3])result = cbind(test_set, y_pred)
nah seperti ini coach
menurut coach bagaimana kalau sprti ini? salah atau benar ya coach?
trimakasihAugust 9, 2023 at 1:08 PM #204060Hi Zulfa,
Untuk warning gapapa dapat diignore saja ya.
Betul untuk factor menggunakan as.factor
Regards
William -
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