I'm trying to set up a random forest classifier in R. It needs to use my csv growth.csv and return a confusion matrix based on the factor "cm".
system
main aar main ek yadrichhik van clasifire sthapit karne kii koshish kar rahaa hum. ise mere CSV vikaas kaa upyog karne kii aavashyaktaa he. CSV or kaarak "CM" ke aadhaar par ek bhram matrix waapas karen.
user
aar librari `randmaforest` main ek bhram matrix banane ke tareeke hai.yah code kaam karnaa chahie:

pustkaalay (yadrichhik)
pustkaalay (dekhbhaal)

# dataset lod karen
data <- read.csv ("grown.csv", sep = ",", header = true)

# sir or aayam pradarshit karen
pradhan data
mand (sir)

# beej set karen
set.seed (100)

# pareekshan or prashikshan data set karen
namoonay <- namoona (nrow (data), 0.8 * nrow (data))
train <- data [namoonay,]
pareekshan <- data [namoonay,]

# yadrichhik van banaaen
model <- randmaforest (semi ~., data = train)

# mulyon kii bhavishyavaanee karen
datapredict <- bhavishyavaanee (model, pareekshan)

# bhram matrix banaaen
ConsubusionMatrix (Datapredict, train $ semi)

yah `randmaforest` or` carat` librari ko aayaat karata he, phir data ko "grow.csv" se `read.csv` ke saath` data` vairieble main lod karata he.yah data ke sir or ayaamon ko pradarshit karata he, phir ek yadrichhik beej set karata he taaki yah sunishchit kiya ja sake ki parinaam phir se beej ke saath bulaae jaaenge.yah aapako ek hi yadrichhik beej kaa upyog karke yadi aavashyak ho to bhavishya main samaan parinaamon kaa utpaadan karne kii anumati degaa.yahaan, yah 100 par set he, lekin aap koi bhi beej chun sakate hai.ek baar beej set ho jane ke baad, yah data ko 80% prashikshan data or 20% pareekshan data main `namoona ()` ke saath tod detaa he or namoonon ke saath `train` prashikshan data or` test` pareekshan data ko paribhaashit karata he.yah `randemforest ()` ke saath yadrichhik van model ko prashikshit karne ke liye prashikshan data kaa upyog karata he, or yah pareekshan data ke aadhaar par bhavishyavaaniyon ko banane ke liye `bhavishyavaanee ()` kaa upyog karata he.ant main, yah aapke dwaara kiye gaye bhram matrix kaa nirmaan karata he, jo aapke dwaara `bhram kii sthiti ()` prashikshan data ke liye bhavishyavaaniyon kii tulana karata he.
assistant
<|system|>
</s>
<|user|>
main aar main ek yadrichhik van clasifire sthapit karne kii koshish kar rahaa hum. ise mere CSV vikaas kaa upyog karne kii aavashyaktaa he. CSV or kaarak "CM" ke aadhaar par ek bhram matrix waapas karen.</s>
<|assistant|>
aar librari `randmaforest` main ek bhram matrix banane ke tareeke hai.yah code kaam karnaa chahie:

pustkaalay (yadrichhik)
pustkaalay (dekhbhaal)

# dataset lod karen
data <- read.csv ("grown.csv", sep = ",", header = true)

# sir or aayam pradarshit karen
pradhan data
mand (sir)

# beej set karen
set.seed (100)

# pareekshan or prashikshan data set karen
namoonay <- namoona (nrow (data), 0.8 * nrow (data))
train <- data [namoonay,]
pareekshan <- data [namoonay,]

# yadrichhik van banaaen
model <- randmaforest (semi ~., data = train)

# mulyon kii bhavishyavaanee karen
datapredict <- bhavishyavaanee (model, pareekshan)

# bhram matrix banaaen
ConsubusionMatrix (Datapredict, train $ semi)

yah `randmaforest` or` carat` librari ko aayaat karata he, phir data ko "grow.csv" se `read.csv` ke saath` data` vairieble main lod karata he.yah data ke sir or ayaamon ko pradarshit karata he, phir ek yadrichhik beej set karata he taaki yah sunishchit kiya ja sake ki parinaam phir se beej ke saath bulaae jaaenge.yah aapako ek hi yadrichhik beej kaa upyog karke yadi aavashyak ho to bhavishya main samaan parinaamon kaa utpaadan karne kii anumati degaa.yahaan, yah 100 par set he, lekin aap koi bhi beej chun sakate hai.ek baar beej set ho jane ke baad, yah data ko 80% prashikshan data or 20% pareekshan data main `namoona ()` ke saath tod detaa he or namoonon ke saath `train` prashikshan data or` test` pareekshan data ko paribhaashit karata he.yah `randemforest ()` ke saath yadrichhik van model ko prashikshit karne ke liye prashikshan data kaa upyog karata he, or yah pareekshan data ke aadhaar par bhavishyavaaniyon ko banane ke liye `bhavishyavaanee ()` kaa upyog karata he.ant main, yah aapke dwaara kiye gaye bhram matrix kaa nirmaan karata he, jo aapke dwaara `bhram kii sthiti ()` prashikshan data ke liye bhavishyavaaniyon kii tulana karata he.</s>
