stedy / machine-learning-with-r-datasets Goto Github PK
View Code? Open in Web Editor NEWFormatted datasets for Machine Learning With R by Brett Lantz
Formatted datasets for Machine Learning With R by Brett Lantz
hi , i have an error in chapter 3.
....
wbcd_n <- as.data.frame(lapply(wbcd[2:31], normalize))
View(wbcd_n)
summary(wbcd_n$area_mean)
wbcd_train <- wbcd[1:469, ]
wbcd_test <- wbcd[470:569, ]
wbcd_train_labels <- wbcd[1:469, 1]
wbcd_train_labels_n <- as.numeric(wbcd_train_labels)
wbcd_test_labels <- wbcd[470:569, 1]
wbcd_test_labels<-as.numeric(wbcd_test_labels)
wbcd_test_pred <- knn(train = wbcd_train, test = wbcd_test, cl = wbcd_train_labels_n, k= 21)
Error in knn(train = wbcd_train, test = wbcd_test, cl = wbcd_train_labels_n, :
NA/NaN/Inf in foreign function call (arg 6)
In addition: Warning messages:
1: In knn(train = wbcd_train, test = wbcd_test, cl = wbcd_train_labels_n, :
NAs introduced by coercion
2: In knn(train = wbcd_train, test = wbcd_test, cl = wbcd_train_labels_n, :
NAs introduced by coercion
i convert variable to numeric but error not resolve.
do you have idea for resolving this error?
tnx.
I'm having mixed results with some of the datasets you've provided. They seem to give different results than in the book. I'm just wondering if you've uploaded datasets here as-is from packt publishing or if you've changed them?
Hi Sir,
Thanks for collating all these datasets.
I am new to ML and not sure how do I download these datasets onto my Mac so that i can practise the R codes.
Can you show me please?
Thanks in advance
Tian
Not a big issue, just make sure it's consistent with the new datasets you uploaded (insurance.csv and others).
Hi,
Great job on downloading the dataset and reformatting them to match the format of the Machine Learning with R by Brett Lantz.
Could you please provide the link to the public domain you got the dataset from?
A declarative, efficient, and flexible JavaScript library for building user interfaces.
๐ Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. ๐๐๐
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google โค๏ธ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.