Linked Questions
11 questions linked to/from When should linear regression be called "machine learning"?
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statistical regression vs machine learning regression [duplicate]
I was trying to understand the difference between statistical regression VS machine learning regression. My background is from Economics and learned regression from statistical point of view for the ...
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The Two Cultures: statistics vs. machine learning?
Last year, I read a blog post from Brendan O'Connor entitled "Statistics vs. Machine Learning, fight!" that discussed some of the differences between the two fields. Andrew Gelman responded ...
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Is there any reason to prefer the AIC or BIC over the other?
The AIC and BIC are both methods of assessing model fit penalized for the number of estimated parameters. As I understand it, BIC penalizes models more for free parameters than does AIC. Beyond a ...
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Differences between cross validation and bootstrapping to estimate the prediction error
I would like your thoughts about the differences between cross validation and bootstrapping to estimate the prediction error.
Does one work better for small dataset sizes or large datasets?
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Solving for regression parameters in closed-form vs gradient descent
In Andrew Ng's machine learning course, he introduces linear regression and logistic regression, and shows how to fit the model parameters using gradient descent and Newton's method.
I know gradient ...
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Why is logistic regression called a machine learning algorithm?
If I understood correctly, in a machine learning algorithm, the model has to learn from its experience, i.e when the model gives the wrong prediction for the new cases, it must adapt to the new ...
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What does the "machine" in "support vector machine" and "restricted Boltzmann machine" mean?
Why are they called "machines"? Is there an origin to the word "machine" used in this context? (Like the name "linear programming" can be confusing but we know why it is called "programming.")
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What is the difference between AI and "normal" programming? [closed]
Based on this link, DL is a subset of ML and ML of AI. My question is, is AI a subset of "normal" programming, or are they the same?
The definition of AI from that link is:
The broad discipline of ...
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Why is it almost impossible to optimize both prediction and explanation?
In my view, it is almost impossible to successfully optimize both accurate prediction of previously unseen observations, and understanding of the phenomenon. Better to focus appropriately.---ljubomir
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What should be called a linear regression? [duplicate]
I've always been puzzled by the discrepancy between several possible terminological uses for such a basic thing as "linear regression":
A certain number of sources just say it corresponds to the ...
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Machine Learning with few observations
Is common to say that Machine Learning techniques represent are purely data driven methods, and them are effective only if we have a large amount of data. I focused here on supervised/predictive ...
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