Questions tagged [bootstraping]

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Bootstrapping formula for TD learning in Reinforcement Learning

In Reinforcement Learning (Sutton & Barto, 2018), p.120, equations (6.3)-(6.4) , to explain the idea of bootstrapping in Temporal-difference learning: \begin{equation} v_{\pi}(s) := E_{\pi}[G_t|...
1 vote
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93 views

What is the best way to combine cross-validation and bootstrapping for one application?

We intend to model data with non-parametric covariate splines and we would like to understand the uncertainty of the parameter estimates/response estimates. Currently, we use cross-validation to model ...
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16 views

Random walk through Bootstrap

I'm performing a Bootstrap Random Walk over a set of points which is a time series with a certain pattern. Right now, I took the set of points and then resample it with replacement. ...
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1 answer
90 views

Understanding bootstrapping in bias variance decomposition

I was going through bias and variance tradeoff article and it makes use of bias_variance_decomp function from mlxtend library. ...
1 vote
0 answers
39 views

How to perform bootstrap validation on CART decision tree?

I have a relatively small dataset n = 500 for which I am training a CART decision tree. My dataset has about 30 variables and the outcome has 3 classes. I am using CART for interpretability purposes, ...
1 vote
0 answers
45 views

Evaluate Dendrogram Statistical Significance

I have N=21 objects and each one has about 80 possible not NaN descriptors. I carried out a hierarchical clustering on the objects and I obtained this dendrogram. I want some kind of 'confidence' ...
0 votes
1 answer
114 views

Perform bootstrapping of an ordinary linear regression model, using B=100 bootstrap resamples of my dataset, and getting RMSE

So Im studying machine learning through R, and Im working with the boston data set from the library MASS. I am practicing bootsrapping. I already carried out analysis to determine how ,many distinct ...
1 vote
0 answers
31 views

Stratified sampling - use of proxy variable

For splitting of the data into train/test/val I use stratified sampling. Is it appropriate to define strata using information extracted from the dataset? E.g. use machine-learning to model proxy ...
2 votes
1 answer
51 views

Question on bootstrap sampling

I have a corpus of manually annotated (aka "gold standard) documents and a collection of NLP systems annotations on the text from the corpus. I want to do a bootstrap sampling of the system and ...
3 votes
2 answers
527 views

List of samples that each tree in a random forest is trained on in Scikit-Learn

In Scikit-learn's random forest, you can set bootstrap=True and each tree would select a subset of samples to train on. Is there a way to see which samples are used in each tree? I went through the ...
1 vote
0 answers
13 views

How are the same observation sets treated in Random Forests with Bootstrapping?

Let's assume an extremely small dataset with only 4 observations. And I create a Random Forest model, with a quite large number of trees, say 200. If so, some sample sets that are the same each other ...
1 vote
1 answer
2k views

nnet in caret. Bootstrapping or cross-validation?

I want to train shallow neural network with one hidden layer using nnet in caret. In trainControl, I used method = "cv" to perform 3-fold cross-validation. The snipped the code and results ...
2 votes
2 answers
224 views

Resampling train and test data in R

I need to try out few different machine learning methods (SVM, Logistic regression etc.), predict a value either true or false, and write down their AUC and Accuracy of these predictions. I have ...
3 votes
0 answers
129 views

Difference Bagging and Bootstrap aggregating

Bootstrap belongs to Efron. Tibshirani wrote a book about that in reference to Efron. Bootstrap process for estimating the standard error of statistic s(x). B bootstrap sample are generatied from ...
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13 views

Estimate class proportions of a feature, central limit theorem

haven't been feeling smart lately and this is probably the most trivial question ever but I really need to know. I'm trying to point estimate some population parameters. I sampled from 1000 randomly ...
1 vote
1 answer
86 views

About confidence/prediction intervals: parametric methods VS non-parametric (via bootstrap) methods

About the methodology to find confidence and/or prediction intervals in, let's say, a regression problem, I know 2 main options: Checking normality in the estimates/predictions distribution, and ...