Linked Questions

4
votes
2answers
2k views

Error increase on L2 regularization in an NN

When introducing L2 regularization on my neural network, there is a point during training where the error starts to increase after having reached a value very close to 0. This is due to the fact that ...
2
votes
2answers
6k views

How much time will xgboost model take?

I have run xg boost model on R. Dataset has 130 columns and 130,000 observations. I have run xgboost model with default parameters, like this- ...
4
votes
2answers
2k views

Understanding lack of fit in logistic regression

How does one interpret the fact that a dataset has a poor fit / lack of fit with respect to a logistic regression model? I can make sense, for example, of a lack of fit in the case of a linear ...
3
votes
2answers
1k views

How to interpret stable and overlapping learning curves?

I have a training data size of about 80k. I plotted a learning curve to check how much of the training sample is required to train the model. Although, after ...
1
vote
1answer
1k views

Why is logistic regression giving a better prediction than linear reg in XGBoost?

I am building a predictive model with 7 features. My target is binary. I have tried using XGBoost in R. ...
3
votes
1answer
1k views

Building random forest and svm in R caret take a very long time

I have searched for that problem but I haven't found a straight forward answer, so I am working with about 1.4 million numeric values and a few train() funtions. Now the problem is with "svmradial" ...
3
votes
2answers
1k views

SVM prediction accuracy drops when using Test data [closed]

I am using the Kaggle Scikit data to learn R. I am using the R e1071 SVM function to predict classes. When I use: ...
4
votes
1answer
1k views

About learning curves in Machine Learning

I am a newbie in the Machine Learning world, I completed the course (very good by the way) of Andrew Ng on Coursera. This question is very software-independent. I would like to know, when you draw a ...
1
vote
1answer
1k views

Underfitting in Logistic Regression

I ran logistic regression on a data of 3700 patients. I have 9 variables and my outcome is presence of a disease or not. I got the regression coefficients and predicted probabilities. When I apply ...
1
vote
1answer
1k views

Interpret learning curves: Training error and validation error are low

I am confused about how to evaluate this result. From this link, it seems like my model is just right, I just want to make sure that my result is a good fit. Any helps would be appreciated. Thanks! ...
3
votes
1answer
340 views

Why does my classical logistic regression model perform better than its elastic net counterpart?

I have about 200 observations and 33 predictors. Due to sample size limitation, I used an elastic net logistic regression model. I have really high specificity ~0.9 but really low sensitivity < 0....
1
vote
1answer
342 views

Over-fitting diagnosis method

How much difference between train and test set errors can indicate over-fitting? For example in logistic regression. I am trying to classify 11746 comments based on their sentiments in three classes ...
3
votes
1answer
520 views

Linear Regression and big data

I have a very large data set ( 79 features: 74 categorical and 5 measurable ) on a very sparse matrix ( 79 x 1,500,000 rows ) The data set is done in this way: phone model, carrier, day of the week, ...
1
vote
1answer
243 views

Model selection procedure for large data sets using cross validation

I have a question about model selection using cross validation. As far as I understood from many other replies related to model selection here, one should use nested cross validation in order to ...
2
votes
1answer
172 views

Diagnostics in smoothing splines

I'm studying about Smoothing Splines and I'm having some doubts about this method. I already understood the criterion to choose the smooth parameter, but How I acess the fit of this type of non-...

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