Linked Questions
33 questions linked to/from Cross-Validation in plain english?
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Cross validation step by step description [duplicate]
I am a statistics novice. I therefore kindly ask for your understanding with this basic question:
I want to cross validate the results of my logistic regression. So far I have divided the overall ...
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Cross Validation - purpose, need and utility [duplicate]
The question might sound like an old one but I haven't got satisfactory answers for a number of questions I have about CV. I looked at several questions on CV here, here, here and here and yet things ...
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Why is cross validation better than training once with the whole data set? [duplicate]
A form of cross validation takes multiple subsets of a data and trains the model on them, then tests on the remaining subsets. Eventually, all subsets will be trained on.
Although I know that ...
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R model developing & validating - Open to Discussion [duplicate]
Throughout my R journey I have noticed the way we can use given data to develop and validate a model.
Assume that you have given data for a problem
train.csv
test.csv
Method A
Combine train+test ...
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Independent assessment of a selected model [duplicate]
The test data set is used for an independent assessment of the selected model, can anybody explain how this process works?
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Measures of model complexity
How can we compare complexity of two models with the same number of parameters?
Edit 09/19: To clarify, model complexity is a measure of how hard it is to learn from limited data. When two models fit ...
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Cross validation and parameter optimization
I have a question about the parameter optimization when I use the 10-fold cross validation.
I want to ask that whether the parameters should fix or not during every fold's model training , i.e. (1) ...
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A mathematical formula for K-fold cross-validation prediction error?
Could anyone elaborate on a theoretical perspective of K-fold cross-validation and especially a mathematical formula for k-fold CV prediction error?
Updated:Could any one of you help me to understand ...
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Reconciling boosted regression trees (BRT), generalized boosted models (GBM), and gradient boosting machine (GBM)
Questions:
What is the difference(s) between boosted regression trees (BRT) and
generalized boosted models (GBM)? Can they be used interchangeably?
Is one a specific form of the other?
Why did ...
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3
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Predicting future values with a regression model
I have a set of predictor variables and a target variable. I am really confused with regards to what method to use for forecasting the target variable.
For example, my data set has monthly customer ...
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Why is it that xgb.cv performs well but xgb.train does not
I am trying to control overfitting using xgboost in R using eta but when I compare the overfitting of my xgb.cv readout to the xgb.train readout, I don't know why <...
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Sample selection algorithms to ensure that training & validation sets are representative
Currently, I am encountering a question, which is how to selection representative samples (training set and test set, even validation set) from the whole data set? I would like build a classification ...
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Cross-validation and logistic regression
I'm interested in building a set of candidate models in R for an analysis using logistic regression. Once I build the set of candidate models and evaluate their fit to the data using AICc (...
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Is it necessary to split dataset for cross validation?
I am using caret package in R for training dataset and cross validation process. I am confused about cross validation process.
Now, i am splitting the dataset to two subset, training and testing;
<...
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what is K in fourier function of R
I am using fourier() function of R which has arguments x,h,K. Can any body please explain me what is 'K' in this function and what is the use of it.
Thanks in ...
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