I use tensorflow to classify my objects in R. I would like to load the model (*.hdf5) and make predictions without the annoying tensorflow messages popping up.
I know how to disable this in python, but not in R. I did not find an R solution in tensorflow & keras documentation.
Would appreciate help.
Related
I am trying to replicate the output obtained in SPSS doing it in R but I do not get the same results. I used the following libraries to help me, but I didn't get the same results as SPSS:
library ("rpart")
library ("readr")
library ("caTools")
library ("dplyr")
library ("party")
library ("party kit")
library ("rpart.plot")
Does anyone know how I could do it? From my research I discovered that at one point there was a library called "CHAID" but now it is no longer available.
I want to build a Bagged Logistic Regression Model in R. My dataset is really biased and has 0.007% of positive occurrences.
My thoughts to solve this was to use Bagged Logistic Regression. I came across the hybridEnsemble package in R. Does anyone have an example of how this package can be used? I searched online, but unfortunately did not find any examples.
Any help will be appreciated.
The way that I would try to solve this is use the h2o.stackedEnsemble() function in the h2o R package. You can automatically create more balanced classifiers by using the balance_classes = TRUE option in all of the base learners. More information about how to use this function to create ensembles is located in the Stacked Ensemble H2O docs.
Also, using H2O will be way faster than anything that's written in native R.
I have implemented randomForest algorithm in R and trying to implement the same using sparkR (from Apache Spark 2.0.0).
But I found only linear model functions like glm() implementations in sparkR
https://www.codementor.io/spark/tutorial/linear-models-apache-spark-1-5-uses-present-limitations
And Couldn't able to find any RandomForest (Decision Tree algorithm) examples.
There is RandomForest in Spark's MLLib but cannot able to find the R bindings for MLLib also.
Kindly let me know, whether SparkR(2.0.0) supports RandomForest? else is it possible to connect SparkR with MLlib to use RandomForest?
If not how can we acheive this using SparkR?
True, it's not available in SparkR as of now.
Possible option is to build random forest on distributed chunks of data and combine your trees later.
Anyways its all about randomness.
A good link: https://groups.google.com/forum/#!topic/sparkr-dev/3N6LK7k4NB0
I want to create a conincidence matrix using R Studio for a decision tree that I have generated. I have done the same in SPSS but am not able to figure out how to do the same in R. I am attaching an image of how it looks in SPSS. If you could point me to the right resource or link that can tell me what the quivalent of this in R is, that would be very helpful. Thank you!!
First, please try and ask targeted questions. What have you tried? What packages have you explored? Where are you getting stuck?
Nonetheless, I would start by reading through this, A Short Introduction to the caret Package. Then, do this:
install.packages("caret")
library(caret)
?confusionMatrix
I was wondering if the functionality given by Weka of building Model trees like M5P which has regression models in the leaves is possible in R. I know there is a way to handle it using the RWeka package. What was somehow strange to me is that the functionality does not exist in other R packages like rpart. The only way to get a "Model Tree" is using the Rweka package?
Thanks for clarification.
Please check cubist and CORElearn packages.