Stack Overflow
Stack Overflow

Questions tagged [gbm]

R package gbm, implementing Generalized Boosted Regression Models library.

R package gbm, implementing Generalized Boosted Regression Models library.

This package implements extensions to Freund and Schapire’s AdaBoost algorithm and Friedman’s gradient boosting machine.

Includes regression methods for least squares,absolute loss, t-distribution loss, quantile regression,logistic, multinomial logistic, Poisson, Cox proportional hazards partial likelihood, AdaBoost exponential loss, Huberized hinge loss, and Learning to Rank measures (LambdaMart).

Who's using gbm?

The gbm package is used in examples in Software for Data Analysis by John Chambers.

gbm is also used in Elements of Statistical Learning by Hastie, Tibshirani and Friedman.

Richard A. Berk also uses gbm in his book, Statistical Learning from a Regression Perspective.

Source: gradientboostedmodels

330 questions
0
votes
1 answer

Is Gradient Boosting regression be more accurate (lower MSE) than the random forest?

I just created a Gradient Boosting model whose out-of-sample prediction is worse than the random forest. The MSE of GBM is 10% higher than the random forest. Below is my sample code. I am sure whether there is any wrong with it. gbm1 <-…
YYY
  • 605
  • 3
  • 8
  • 16
0
votes
0 answers

R: A very big cross-validation error

I have 303 data points in the train set (see the picture). Many of these points are equal to 0 on the Y axis. Now I want to train the GBM model to predict the Y value. Here is my model: train.subset<- data.frame(yval=train$yval, …
Klausos Klausos
  • 15,308
  • 51
  • 135
  • 217
0
votes
1 answer

GBM and Caret package: invalid number of intervals

Though I am defining that target <- factor(train$target, levels = c(0, 1)), the below-given code provides this error: Error in cut.default(y, unique(quantile(y, probs = seq(0, 1, length = cuts))), : invalid number of intervals In addition:…
Klausos Klausos
  • 15,308
  • 51
  • 135
  • 217
0
votes
1 answer

Possible bug in Caret function predict.gb()?

It seems to me that I’ve discovered a bug in the performance of the predict() function for method=gbm in the Caret package in R. I'm curious to know if others agree, or if someone has an explanation for the behavior of this function. 1. Generate…
Jeff W
  • 1
0
votes
1 answer

can't delete y axis label in plot.gbm

Run-on question following this problem setting axis widths in gbm.plot; I'm now using plot.gbm directly and don't seem to be able to remove the y axis label, which seems to be set within the plot.gbm function…
dez93_2000
  • 1,730
  • 2
  • 23
  • 34
0
votes
1 answer

(R) Axis widths in gbm.plot

Hoping for some pointers or some experiences insight as i'm literally losing my mind over this, been trying for 2 full days to set up the right values to have a function spit out clean simple line plots from the gbm.plot function (packages dismo &…
dez93_2000
  • 1,730
  • 2
  • 23
  • 34
0
votes
1 answer

Grandient Boosting Regressor : "TypeError: cannot perform reduce with flexible type"

I am new in python and I am trying to developp a program with Gradient Boosting Regressor. I have two big sets of data, one training set and one test set in wich I have exactly the same columns. My goal is to predict the SeriousDlqin2yrs column of…
user3471868
  • 1
  • 1
  • 1
0
votes
1 answer

Representing a class by negative number for training in GBM in R

I have already generated a huge train file of ~1GB in which the ground truth is one of 4 classes {-1,0,1,2}. Yes, I agree that I could have done it using 3 instead of -1, but for some conventional reasons I used -1. I want to use gbm in multinomial…
Bit Manipulator
  • 248
  • 1
  • 2
  • 17
-1
votes
1 answer

How to find the optimum number of estimators using "OOB" method in sklearn boosting?

The gbm package in R has a function gbm.perf to find the optimum number of trees for the model using different methods like "Out-of-Bag" or "Cross-Validation" error, which helps to avoid over-fitting. Does Gradientboosting inScikit learn library in…
lakshman thota
  • 11
  • 5
-1
votes
1 answer

can i take best parameters and best model of optuna function and apply this model directly in my notebook?

i esttablished a function of optuna to find out best model of gbm and xgboost for my data but i was wondering if i can take the best model and apply it directly into my notebook(extracting best model as an object to reuse it later) here is my…
Baraa najjar
  • 73
  • 7
-1
votes
1 answer

Why does my code take so long to process?

I try to run code from this web site in my computer. I use data set from kaggle competition In my training data 1022 rows and 81 variables. I run this code: hyper_grid <- expand.grid( shrinkage = c(.01, .1, .3), interaction.depth = c(1, 3, 5), …
Ekaterina
  • 69
  • 8
-1
votes
1 answer

Getting probability values for random forest and Gradient Boosting in python

I have been learning about classification techniques and studied about random forest, gradient boosting etc.Based on some help from codes available online,i tried to write code in python3 for random forest and GBM. My objective is to get the…
Krish Basu
  • 1
-1
votes
1 answer

Poor h2o GBM Classification Performance in a balanced binomial response

In a fairly balanced binomial classification response problem, I am observing unusual level of error in h2o.gbm classification for determining class 0, on train set itself. It is from a competition which is over, so interest is only towards…
Hari Prasad
  • 1,751
  • 2
  • 15
  • 20
-1
votes
1 answer

GBM cross validation

I'm trying to use R's gbm regression model. I want to compute the coefficient of determination (R squared) between the cross validation predicted response values and the true response values. However, the cv.fitted values of the gbm.object only…
dan
  • 6,048
  • 10
  • 57
  • 125
-3
votes
1 answer

R, Caret, train(), predict(), GBM, Error: Error in model.frame.default(..): Factor has new levels

So I have a pretty good idea of what is happening but I'm wondering how to handle the error, I've seen other posts similar to this but they were not specific to Gradient Boosting Machine models. They all seem to be related to GLMs and the error…
Factuary
  • 43
  • 1
  • 8
1 2 3
…
21
22