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Model evaluation approach allowing manual experimentation without data leakage

In supervised machine learning, are there any evaluation approaches beside using a fixed holdout test dataset, which allow me as a scientist to manually compare preprocessing approaches, without ...
thomas8wp's user avatar
  • 111
0 votes
0 answers
31 views

Understanding the code for calculating the 95% confidence interval of AUC using bootstrapping

It's really embarrassing, but I lack statistical knowledge. I would like to find the confidence interval for AUC at 95%. Actually, I got the code from here(https://stackoverflow.com/questions/52373318/...
JAE's user avatar
  • 13
3 votes
2 answers
146 views

How bootstrapping works for prediction intervals?

I'm experimenting with prediction interval (PI) over univariant time-data using skforecast pythonic package.. in the documentation it is mentioned that: Prediction intervals A prediction interval ...
Mario's user avatar
  • 400
0 votes
0 answers
36 views

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|...
fermented_bean's user avatar
1 vote
0 answers
190 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 ...
Stan Tendijck's user avatar
0 votes
1 answer
167 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. ...
Mahesha999's user avatar
1 vote
0 answers
62 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, ...
Eric Yamga's user avatar
1 vote
0 answers
59 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' ...
Mirko's user avatar
  • 111
1 vote
0 answers
33 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 ...
holoubekm's user avatar
3 votes
2 answers
600 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 ...
theonionring0127's user avatar
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 ...
jlee's user avatar
  • 11
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 ...
SiH's user avatar
  • 125
3 votes
0 answers
139 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 ...
martin's user avatar
  • 329
0 votes
0 answers
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 ...
Laurent's user avatar
  • 53
2 votes
2 answers
262 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 ...
znoris007's user avatar
2 votes
1 answer
59 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 ...
horcle_buzz's user avatar
0 votes
1 answer
137 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 ...
Robbie Meaney's user avatar
1 vote
1 answer
98 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 ...
German C M's user avatar
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