Questions tagged [bias]
The bias tag has no usage guidance.
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How to adjust classification totals based on known bias of estimator
Let's say I have a dataset, $D$, with known ground truth labels. I nonetheless use a few-shot LLM classifier on this dataset to predict $k$ classes for each label.
From the LLM results, I get ...
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Is always low bias and low variance desirable?
Assume we have two regression models M1 and M2 for a given data. Assuming M2 has lower bias and lower variance, would you always consider using this? This example shows that if the data is random ...
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How do I compute and plot Bias and Variance of a classifier in Python?
I'm new to Machine Learning and I understand bias and variance in theory but I can't seem to find a single source that explains how bias or variance can be computed. I'd like to do it in Python and ...
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ML development on data biased by historical treatments
I have a dataset where in each data point was subject to certain treatment (4 different treatments) in the past based on their riskiness. The riskiness was estimated by a logistic regression model in ...
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Model performance impact on social discrimination?
I am currently working on a project where the data concerns people and the dataset contain personal data with sensitive attributes. (typically: age, sex, handicap, race).
Now it seems there are mainly ...
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Question about bias-variance trade off
This question is from a uni module about machine learning. I'm a bit stuck as I can't relate it to the bias-variance trade-off, to me the question implies all models have something to do with the ...
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Neural regression predictions all around the mean of target
I have a transformer regression model and some data about last users transactions (categorical and numerical). My target has exponential distribution with mean aroud 10e4 and also zero-inflated, so I ...
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AB testing: Control was performing 0.5% better than experiment set before the initiation of experiment
So we introduced a new feature in our app, that would aid conversion (hypothetically).
When i tried to measure this incremental change in conversion, i split my base set of customers into control(C) ...
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How do I know If my regression model is underfitting?
How do we evaluate the performance of a regression model with a certain RMSE given that a domain knowledge performance metric is not present?
Maybe MAPE is one way of comparing the performance of my ...
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Bias-Variance Bulls-Eye Diagram: high variance and high bias
Often bias/variance trade-off is explained by a Bulls eye diagram. I like the explanation in the linked webpage but it doesn't answer the question how a model that has high variance and high bias ...
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Is Logistic Regression possible using a Convenience Sample?
I've collected some survey data on homeless individuals, surveying their drug use, education level, age, gender etc. I hope to run a logistic regression to see how impactful homelessness (+other ...
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Understanding bootstrapping in bias variance decomposition
I was going through bias and variance tradeoff article and it makes use of bias_variance_decomp function from mlxtend library. ...
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Bias that makes annotators accept a prediction rather then coming up with a different label
Many annotation tools can speed up the classification of images (or other data) by providing a prediction of the correct label which the user can accept or correct.
However, humans have a tendency to ...
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pytorchs LSTMs use of 'bias' and 'weight' strings
Hi I am new to RNN and have come across this the following implementation of Pytorchs LSTM, but I cant understand how (or why) the 'bias' and ...
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Proof for MSE = Var + Bias2
I am trying to prove the equality of $$\rm MSE=Var+Bias^2$$ but obviously I got something wrong as they don't equal in my calculation:
So here is the example. I use monte carlo to estimate this ...
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