Linked Questions
11 questions linked to/from When will a less true model predict better than a truer model?
62
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7
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Intuitive explanation of the bias-variance tradeoff?
I am looking for an intuitive explanation of the bias-variance tradeoff, both in general and specifically in the context of linear regression.
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71
votes
5
answers
17k
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What problem do shrinkage methods solve?
The holiday season has given me the opportunity to curl up next to the fire with The Elements of Statistical Learning. Coming from a (frequentist) econometrics perspective, I'm having trouble grasping ...
- 14.2k
13
votes
3
answers
7k
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How can you handle unstable $\beta$ estimates in linear regression with high multi-collinearity without throwing out variables?
Beta stability in linear regression with high multi-collinearity?
Let's say in a linear regression, the variables $x_1$ and $x_2$ has high multi-collinearity (correlation is around 0.9).
We are ...
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8
votes
4
answers
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Is MSE decreasing with increasing number of explanatory variables?
I am wondering, if there is a negative correlation between Mean Squared Error
\begin{equation}
MSE = \frac{1}{n} \sum (\hat{Y}_i - Y_i)^2
\end{equation}
and the number of explanatory variables. ...
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20
votes
2
answers
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Is there a graphical representation of bias-variance tradeoff in linear regression?
I am suffering from a blackout. I was presented the following picture to showcase the bias-variance tradeoff in the context of linear regression:
I can see that none of the two models is a good fit - ...
- 2,650
8
votes
4
answers
3k
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Why must one trade off between bias and variance?
Apparently, a learning algorithm must make a trade off between bias and variance when producing a hypothesis. Bias means systematic deviation from data. Variance refers to the error due to ...
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1
vote
1
answer
910
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When should you check if assumptions are met when using stepwise selection?
Suppose I want to find a linear model with Gaussian error for a given data set. (The data set contains insurance claims and the end goal is to predict claim cost from claim features.) Also, suppose ...
- 229
1
vote
1
answer
1k
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How to improve this logistic regression model
I am using following data and self-explanatory code to create a model for prediction of 'low' (low birth weight) from modified birthwt dataset. I am using 80% for training and 20% for testing:
...
- 10.1k
10
votes
1
answer
592
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About the meaning of ARMA parameters
I suppose that the main scope of an econometric models should be predictive or causal inference. Following this perspective it was shown that underspecified model can perform better than the correct ...
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15
votes
0
answers
867
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Practical thoughts on explanatory vs predictive modeling [duplicate]
Possible Duplicate:
Practical thoughts on explanatory vs. predictive modeling
This question has been bugging me for some time, and I was going to write a blog post about it. However, I think it ...
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2
votes
3
answers
134
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Choice of a less true model over the truer model if it predicts better and my purpose is prediction
Sometimes a less true model predicts better than a truer model (When will a less true model predict better than a truer model?). So should I choose a less true model over the truer model if it ...
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