Questions tagged [train]

training (or estimation) of statistical models or algorithms.

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201
votes
5answers
144k views

Tradeoff batch size vs. number of iterations to train a neural network

When training a neural network, what difference does it make to set: batch size to $a$ and number of iterations to $b$ vs. batch size to $c$ and number of iterations to $d$ where $ ab = cd $? To ...
12
votes
1answer
7k views

How to know if a learning curve from SVM model suffers from bias or variance?

I created this learning curve and I want to know if my SVM model suffers from bias or variance? How can I conclude that from this graph?
11
votes
4answers
1k views

Good examples/books/resources to learn about applied machine learning (not just ML itself)

I've taken an ML course previously, but now that I am working with ML related projects at my job, I am struggling quite a bit to actually apply it. I'm sure the stuff I'm doing has been researched/...
17
votes
3answers
8k views

Imputation before or after splitting into train and test?

I have a data set with N ~ 5000 and about 1/2 missing on at least one important variable. The main analytic method will be Cox proportional hazards. I plan to use multiple imputation. I will also be ...
2
votes
1answer
3k views

How to correctly use validation and test sets for Neural Network training?

I am in the machine learning business for a long time, but still, this fundamental fact gets me confused, since every paper, article and/or book describe different kind of usages for validation and ...
7
votes
4answers
11k views

How to train a Gaussian mixture hidden Markov model?

I want to build a hidden Markov model (HMM) with continuous observations modeled as Gaussian mixtures (Gaussian mixture model = GMM). The way I understand the training process is that it should be ...
3
votes
1answer
76 views

Does retraining a model on all available data necessarily yield a better model?

A (simplified) typical workflow in machine learning might be: Train $m$ models on a training set. Validate the $m$ models on a validation set to yield the best model with parameters $\theta$. Retrain ...
2
votes
0answers
1k views

Are RSS and R^2 related to training error only?

While reading An Introduction to Statistical Learning, I stumbled across the following (p. 210): [...] the model containing all of the predictors will always have the smallest $RSS$ and the ...
2
votes
1answer
349 views

Amount of training data for classification accuracy

Is there an intuition or any relevant reading about the relationship between dimensionality of data, number of samples, model complexity and test accuracy of classification? E.g. for the simple cat/...
8
votes
1answer
574 views

How can the AIC or BIC be used instead of the train/test split?

I've recently come across several "informal" sources that indicate that in some circumstances, if we use the AIC or BIC to train a time series model, we don't need to split the data into test and ...
0
votes
1answer
2k views

Creating a test set with imbalanced data

I am working on a binary random forest using R. mu data set consists of 300 cases classes 1 and 2100 cases class 0. I am planning to evaluate my model using the model prediction and the AUC and for ...
2
votes
2answers
4k views

after using cross-validation, is a separate train-test split necessary for generating a model?

I am going through the excellent book "Introduction to Machine Learning with Python," and reading about cross-validation. I can understand how it makes a more efficient use of the data than a typical ...
10
votes
3answers
406 views

Approaches when learning from huge datasets?

Basically, there are two common ways to learn against huge datasets (when you're confronted by time/space restrictions): Cheating :) - use just a "manageable" subset for training. The loss of ...
1
vote
2answers
183 views

Imputing the mean value from the 'train set' into the 'test set'

I have looked at a couple questions and answers similar to this, the recommendation seems to be the imputation of mean values from the 'training set' into my 'test set'. However, what I am trying to ...
6
votes
4answers
3k views

Does increase in training set size help in increasing the accuracy perpetually or is there a saturation point?

I am using a boosted trees classifier which is giving better accuracy then all other linear classifier I tried. I have almost an unlimited training data at my disposal , I wanted to know if there is a ...
2
votes
0answers
372 views

CV.glmnet results [duplicate]

I was working through the lab on ridge regression and LASSO in ISLR and I came across a strange behavior in the cv.glmnet function. When I followed the lab as ...
0
votes
3answers
302 views

How to quantitatively determine when to stop training ANN

I've implemented an artificial recurrent neural network and want to start training it on a variety of tasks. I've extensive searching online and haven't found a satisfactory answer of how the ...
0
votes
1answer
42 views

Duplicates in feature matrix

I have several points which appear duplicates in the feature matrix (same values for the features). These points may have different values of the target variable. What is the appropriate way to handle ...
0
votes
1answer
1k views

Extracting Standard Errors Caret Model

I have tuned a glm net model with caret using the train function. I am trying to extract the coefficients and standard errors of those coefficients for the best tuned model. Following this CV post I ...