The gbm tag has no wiki summary.
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How does cross validation work in R's gbm package?
Can someone provide a work flow about this? For instance, suppose I am doing binary classification,
For each iteration of the algorithm:
Randomly sample k*N rows, where k is the bag.fraction, and N ...
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Machine Learning Algorithms vs. Linear Regression
Do machine learning algorithms like Boosted Regression Trees (in the R package (gbm)) follow the same statistical assumptions of not including correlated predictor variables in GLM?
i.e. If I have ...
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has anyone implemented an autoencoder with random forests
I'm interested in exploring autoencoders which can be used to develop a compressed representation of data useful for machine learning.
In my experience random forests are easier to work with and more ...
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Model Matrix and GBM
I am using the GBM package to create a prediction model. Can GBM handle categorical predictors, or do I need to create a model matrix before I input ?
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How to use R gbm with distribution = “adaboost”?
Documentation states that R gbm with distribution = "adaboost" can be used for 0-1 classification problem. Consider the following code fragment:
...
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222 views
GBM relative influence
For a regression problem, I used gradient boosting machines and assessed RMSE. My dataset is comprised of 34 features and 10,000 records. Only 2 predictors were considered 'important' (importance for ...
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206 views
Strategy to set the GBM parameters
I would like to know how you would set the parameters for the GBM model?
1)
I could optimize the parameters sequentially. At first, using a large value for shrinkage and a small number of iterations ...
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GBM Predictions - Different results for similar approaches
I am new to R and programming in general and need some help. I am trying to find if a population having a certain characteristic is better than the population that does not have it. Lets say, it's the ...
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Modifying package gbm of R [closed]
We are trying to experiment using the gbm package on a quite large dataset (~140 million rows) and we have ran into a problem with the memory requirements of R.
We have tried combining the packages ...
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Classification with GBM in R and imbalanced class sizes
I'm dealing with a supervised binary classification issue. I'd like to use the GBM package to classify individuals as uninfected/infected. I have 15 times more uninfected than infected individuals.
I ...
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1answer
164 views
Does the 'fit' attribute of a gbm object contain the OOB estimates?
I have looked at the help (?gbm) and documentation for gbm.object, it only says that
fit: a vector containing the fitted values on the scale of
regression function (e.g. log-odds ...
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227 views
Role of n.minobsinnode parameter of GBM in R [closed]
I wanted to know what the n.minobsinnode parameter means in the GBM package. I read the manual, but it is not clear what it does.
Should that number be small or large to improve the results?
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What are some useful guidelines for GBM parameters?
What are some useful guidelines for testing parameters (i.e. interaction depth, minchild, sample rate, etc.) using GBM?
Let's say I have 70-100 features, a population of 200,000 and I intend to test ...
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179 views
How to calculate fitted values when using AdaBoost via gbm package in R? What does fitted values mean?
I poseted this question about two weeks ago. But it was closed because I cross-posted here and on SO. So I deleted the post on SO and re-post here. My question is as below.
First of all I'm not ...
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248 views
How to calculate fitted values when using AdaBoost via gbm package in R? [closed]
First of all I'm not good at English. So please be patient to interpret my words. I really need your help.
I used the R package GBM as probably my predictive modeling. I made a model with adaboost ...
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What does interaction depth mean in GBM?
I had a question on the interaction depth parameter in gbm in R. This may be a noob question, for which I apologize, but how does the parameter, which I believe denotes the number of terminal nodes in ...
