Questions tagged [bias]
The difference between the expected value of a parameter estimator & the true value of the parameter. Do NOT use this tag to refer to the [bias-term] / [bias-node] (ie the [intercept]).
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How to compute the expected value of the ridge regression estimator?
I am trying to understand this derivation:
I think everything except the last equality is fairly simple, but I do not understand the last equality. Is there an error here?
I appreciate any help.
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How to deal with Bias Gradient Matrix for biased CRB(Cramér–Rao bound) calculation if the gradient matrix is m-by-n but $m \neq n$?
I am doing a model for collabrative localization and using the CRB(Cramér–Rao bound) as the localization performance measurement. I want to consider interference caused by NLOS and clutter, therefore ...
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Why is the threshold term incorporated into the weight vector in linear classifiers?
In the context of linear classifiers, such as the perceptron or logistic regression, I understand that the decision boundary is defined by a linear combination of input features and weights, plus a ...
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Expectation of reciprocal residual sum of squares
Consider an IID sample $X_1 , \cdots, X_n \in \mathbb{R}^d$, then what can we say about the expectation of the reciprocal residuals when projecting onto every other point? That is can we compute
$$
E \...
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How to get an unbiased estimator
Defining the sample mean as $\bar{x} = \frac{1}{N}\sum_{n=0}^{N-1}x_n$, and having $N$ realizations of a random variable $x$ with mean $\mu$ and variance $\sigma^2$
Defining $\bar{x}^2=\hat{\mu^2}$, ...
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Omitted variable bias formula for 3 variable regression
Suppose our true model is:
$Y=\alpha +\beta_{1} X_{1}+\beta_{2} X_{2}+\beta_{3} X_{3}+u$
but instead, we omit $X_{3}$ and estimate the following by OLS:
$Y=\alpha +\beta_{1} X_{1}+\beta_{2} X_{2}+v$...
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Can unbalanced classes introduce bias in a Random Forest model?
I am working on a classification problem using Random Forest.
The training set has 600 instances and 16 attributes. The final class is an Yes/No answer. The ratio of "Yes" to "No" in the training ...
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A case of survivorship bias?
With the recent FIFA world cup, I decided to have some fun and determine which months produced world cup football players. Turned out, most footballers in the 2010 world cup were born in the first ...
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Interpreting differences between confidence intervals with and without adjustment for clustering. Should those from adjustment be wider?
I am trying to interpret an article involving data from a cluster randomised trial, where the confidence intervals for effect sizes are said to have been adjusted 'using the standard errors of the ...
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Why do top-down approaches produce biased coherent forecasts?
The context is forecasting hierarchical time series. Section 10.4 of "Forecasting: Principles and Practice" (2nd edition) by Hyndman & Atahnasopoulos states:
One disadvantage of all top-...
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How error derivative becomes zero in gradient descent
Previous questions this & this does not answer my question
Code
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Does bias in statistics and machine learning mean the same thing?
In statistics, people often talk about unbiased estimators. In machine learning, bias variance trade-off is mentioned all the time.
Does bias in both contexts mean the same thing?
Does an unbiased ...
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Why does increasing model complexity reduce bias over the entire data distribution?
In ML, we often talk about the bias-variance tradeoff, and how increasing model complexity both reduces bias and increases variance. I understand why increasing model complexity reduces bias at first, ...
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Experimental Design questions
I have a couple of questions regarding the procedures in an experiment. If I would like to test out two different drugs and the effect it has on the subject, why would it be a good idea to randomize ...
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What to show as error-bar if the bootstrap distribution is biased?
Say I have a sample, of finite size $N$, and I compute some statistic $\theta$ from it. I want to plot this sample estimate, $\hat{\theta}$, with an error-bar.
To compute the error, I am using ...
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