Tagged Questions

0
votes
1answer
35 views

What's the difference between bias in model error in regression?

Is model error the same as bias in regression? For example, if I construct data by $y_i=N^{\text{th}}$ degree polynomial plus uncorrelated noise, and do a regression with the $M^{\text{th}}$ degree ...
2
votes
1answer
80 views

Confusion related to the bagging technique

I am having a bit of confusion. I was reading this paper where it explained that bagging technique greatly reduces variance and only slightly increases bias. I didn't get it how come it reduces ...
4
votes
1answer
152 views

Bias of variance/precision estimator using Gamma prior

Assume I have $N$ samples $x_1, \cdots, x_N$ from a Gaussian random variable $X\sim N(\mu, \sigma^2)$ where both $\mu$ and $\lambda = 1/\sigma^2$ are unknown. If I apply MLE, I have $\mu_{MLE} = ...
0
votes
1answer
78 views

Learning Curves Example

I'm trying to find a full example of how to plot learning curves. I watched Andrew Ng's ML class on Coursera and he mentions using learning curves to diagnose variance-bias issues. My notes show ...
0
votes
0answers
136 views

Improving accuracy of total variance through variance components?

I'm following a measurement guidance that specifies a technique to improve the estimate of total variance by extracting individual variance components and performing a sum of squares. I'm not a ...
2
votes
0answers
89 views

Generalized Linear Models and Curse of Dimensionality

I was wondering what happens to bias and variance of GLM estimates as dimensionality approaches the number of training data points? Specifically in Linear Regression and Poisson Regression? I know ...
1
vote
0answers
82 views

When “additive modeling” is better?

Given $y=f(x)+\epsilon$ where $x=(x_1,\dots,x_p)$, $f$ is highly non-linear and two different estimators: $\hat{y}=\hat{M}(x)$ $\hat{y}=\hat M_1(x)+\hat M_2(x)$ where $M_1$ is a simple (biased) ...
10
votes
2answers
503 views

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 ...
4
votes
0answers
220 views

Expected value of the natural log of a ratio of variances [closed]

I am dealing with a one-way random effects model and am looking for the $E(\ln(\hat{\sigma}_\alpha^2/\hat{\sigma}^2))$ where $\hat{\sigma}_\alpha^2$ is the estimate of the between group variance and ...