Questions tagged [huber]
The huber tag has no usage guidance.
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Huber loss problem for object localization
Object localization refers to finding a bounding box for an object in a frame for the purpose of object detection.
I have read here on page 2 that Huber loss has a problem in object localization as it ...
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Huber and tweedie regression - Feature importance and Interpretation
Am currently working on a regression problem to predict the revenue of a customer.
As my data exhibits slight non-linearity, the best performing models for my dataset are the below
a) Huber Regressor
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Does it make sense that the loss function for traning and evaluaton is different?
Huber loss function is widely used, because it combines the good properties of squared and absolute losses. Therefore, when I apply the penalized regressions, i.e. LASSO, Elastic net and Ridge, to ...
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Reporting robust means and SD to make more comparable to robustbase::glmrob results
I need to report the mean, and SD of two groups for a specific variable, as well as the odds ratio of the two groups using robust logistic regression. The variable does have outliers. I instead want ...
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Question about Huber loss when k=0 in Casella and Berger
In Casella and Berger (page484), the following Huber loss is defined.
Then on the next page, Table 10.2.1 shows the Huber estimator for different $k$:
In particular, $k=0$ gives the median, which ...
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Minimizing Huber Loss
Huber Loss is given as follows:
I'd like to proof $\gamma=median\{y_1,...y_N \}$ minimizes the Huber Loss so i've taken its first derivate for $\gamma\neq y_i$:
I've tried to proof that first ...
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Convex set of huber's contamination model
In the celebrated Huber's robust estimation paper, he considered the following model
$x_i \sim (1-\epsilon) P_\theta + \epsilon G$ where $P_\theta$ is assume to be standard normal. Under this model, ...
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Why is there no improvement when training Xgboost with pseudo-Huber loss?
In this StackOverflow post I asked if there was something wrong with my syntax when training an XGboost model (in R) with the native pseudo-Huber loss ...
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In general, how to determine the weight function of Robust regression
I think the question is clear from the title.
How the weight function for example in Huber is calculated?
Is it by differentiating the objective function?
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How to choose delta parameter in Huber Loss function?
In Huber loss function, there is a hyperparameter (delta) to switch two error function. Currently, I am setting that value manually. But, I cannot decide which values are the best.
So, how to choose ...
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Existence of Huber M-estimators
I am working on a paper about optimization using the Huber's Loss function, which is defined as:
\begin{equation}
\psi(x)=\begin{cases} \frac{x^2}{2\gamma},& \text{if } \lvert x\rvert\leq\gamma\\
...
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Tradeoffs of robust mean measures (trimmed, Huber, cosh, etc)
After recently having delved into the world of robust measures (for location, mean being the classical case), I have had difficulty understanding robust measures' core dynamic. Basically, what are ...
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How is the parameter „huber_alpha“ defined in H2O Deep Learning?
In the documentation of the H2O software (http://docs.h2o.ai/h2o/latest-stable/h2o-docs/data-science/deep-learning.html) it says for the parameter “huber_alpha: Specify the desired quantile for Huber/...
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Huber Loss on top of Cross Entropy
I know that the Huber loss is usually applied on top of the L2 loss in order to prevent exploding gradients. Does it make sense to use the Huber loss on top of the cross entropy loss, though? I have a ...
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Scikit-learn: How to normalize Huber regressors?
In scikit-learn the Ridge regression estimator has a normalize parameter that normalizes the regressors. I found that it was necessary to set this to ...
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functional differences between using huber loss and winsorizing/trimming
Curious what the functional differences are between using a Huber loss function/ regression and Winsorizing data and then running a classic least squares regression.
Will the resulting outputs be ...
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