1
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Whether Chi-square statistic Test helps us to assess a non-linear correlation between two categorical variables?
I'm not sure that "linear" and "non-linear" are the appropriate terms here. When $x$ and $y$ have a linear relationship, it means that when $x$ changes by $\Delta$, $y$ changes by ...
1
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Two computers, different outputs for same code in R studio
Your classmate obtains a p-value which is exactly half of the one you have. This is precisely what would happen if you run the test with two-sided as value of ...
1
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what are the main differences between parametric and non-parametric machine learning algorithms?
Non-parametric machine learning algorithms try to make assumptions about the data given the patterns observed from similar instances. By not making assumptions, they are free to learn any functional ...
1
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Accepted
Books about statistical inference
For theory Tibshirani: The elements of statistical learning
https://web.stanford.edu/~hastie/Papers/ESLII.pdf
Also Andrew NG and other books from deeplearning.ai:
Machine Learning Yearning
https://...
1
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Accepted
Logic behind the Statement on Non-Parametric models
Non-parametric machine learning algorithms try to make assumptions about the data given the patterns observed from similar instances.By not making assumptions, they are free to learn any functional ...
1
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Do non-parametric models always overfit without regularization?
No - non-parametric methods only means that the method does not assume a function form of the data. There are non-parametric methods such as Random Forest that do not always overfit. In fact ...
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Good introductory reference for Bayesian Non-parametric (Dirichlet Process / Chinese Restaurant Process)
I would recommend Tamara Broderick's 3-part tutorial series from MLSS. She explains both modeling + inference using these methods from the ground up and focuses on the intuition.
Links to part 1, ...
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