Questions tagged [c5.0]
37 questions
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lift in c5.0 rules -what is lift?
can someone assist in explain what is the lift i.e
Rule 1: (2554/165, lift 1.3)
Contract in {One year, Two year}
-> class No [0.935]
what is the 1.3 in the lift
zachi
- 511
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- 13
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1 answer
could not find function "C5.0 r using C50
I would like to use C5.0 but with few error
this is the code:
library(modeldata)
data(credit_data)
set.seed(2411)
in_train <- sample(1:nrow(credit_data), size = 3000)
train_data <- credit_data[ in_train,]
test_data <-…
zachi
- 511
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- 13
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I am using the C5.0 algorithm to construct a decision tree and it uses only one of the variables that I feed it. How do I force it to be more complex?
The variable in question is the most informative one (sorry if the language is bad, Im a newbie), and the tree is 90% accurate (base rate would be around 86%), however I want the algorithm to use more than one attiribute. I constructed a CART tree…
juliusz799
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- 1
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Error in plotting C5.0 decision tree : how can I make proper model?
This is my Jogging data.
WEATHER JOGGED_YESTERDAY CLASSIFICATION
C N +
W Y -
Y Y -
C Y -
Y N -
W Y …
kang yep sng
- 73
- 4
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Why does C5.0 algorithm return a tree of size 1 with highly imbalance dataset?
I have extremly imbalanced dataset with two classes and 15 predictors, where my goal is to predict the minority class. The minority class constitutes 0.074% of the data with 1 624 577 samples. I am tuning the models with 5-fold cross-validation and…
Samuel Pazicky
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- 1
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I wonder how to solve the problem of factor outcome or class logical in the C5.0 model
xdata <- credit_train[,-17]
ydata <- credit_train[,17]
treeModel <- C5.0(x=xdata,y=ydata)
Error: C5.0 models require a factor outcome
I specified it as a factor in the above error, but the following error occurred
xdata <- credit_train[,-17]
ydata…
anne
- 1
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1 answer
Why do I get 'c50 code called exit with value 1' in R?
I am using RStudio 2021.09.0 "Ghost Orchid" Release for macOS.
I am learning to use to C5.0 algorithm in R. For this I am following 'Machine Learning in R' by Brett Lantz. The dataset I am using is a modified version of one relating to loans…
for_the_love_of_cod
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- 5
0
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1 answer
Getting more information about C5 model in tidymodels
Here's a simple modelling workflow using the palmerpenguins dataset:
library(tidyverse)
library(tidymodels)
#> Registered S3 method overwritten by 'tune':
#> method from
#> required_pkgs.model_spec parsnip
#> Warning:…
Desmond
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- 14
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R C5.0: Error while including minCases in tunegrid (caret)
i am trying to implement the minCases-argument into my tuning process of a c5.0 model.
As i am using the caret package i am trying to get that argument into the "tuneGrid".
For that purpose i found the following…
Lars
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error in plot function (variable match was not found)
i am trying to plot my decision tree, but it keeps giving me this error, and i can not figure out what is wrong.
here's the…
pinky_dinky_doo400
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- 5
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0 answers
> plot(model) Error in FUN(X[[i]], ...) : Variable match was not found
library(C50)
model <- C5.0(training$`Class variable`~ ., data = training[, -9])
plot(model)
pred <- predict.C5.0(model, testing[, -9])
a <- table(testing$`Class variable`, pred)
sum(diag(a))/sum(a)
here while plotting my model i am getting this…
0
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1 answer
Extract Rules from Trained C5.0 Model in Tidymodels
I could and should have made a simpler reprex, but this is really straight out of my work.
After training a C5.0 model in the Tidymodels framwork, how do I "see" the rules that the model generated?
I tried to replicate what is illustrated…
larry77
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What is this error caused by in this cross-validation model training?
The dataset used here has also been used in another model and it worked. Also, the C5.0 method has been used with another dataset and worked as well:
> fitControl<-trainControl(
+ method=cv",
+ number=10)
+ set.seed(100)
+…
Kai7
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- 5
0
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0 answers
The R "summary(model)" command never completes after train() with carot package (k-fold cross validation)
The summary(model) command never completes.
K-fold cross validation was ran as follows (R caret package):
train_control <- trainControl(method="repeatedcv", number=10, repeats=0)
model <- train(as.factor(OneGM) ~., data=OneT,…
user13248694
0
votes
1 answer
Why my decision tree have not node? (C5.0)
I have 204 data with 6 atribute.
When i create the model with all data with this script, model = C5.0(dataset1[,-7], dataset1[,7]),
the result give me no node like the picture below.
But, if i just use 100 data with this script, model =…
ferdianm10
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