Jiayang Nie
Jiayang Nie
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Feature Engineering - Common Methods to Select Features with Pros and Cons
https://medium.com/@niejiayang32/common-methods-to-select-features-with-pros-and-cons-efd71e2a1f01
Last updated on May 20, 2022
1 min read
How does R solve linear regression?
The time complexity for using the closed-form solution is very high. In R, unlike other package that uses gradient descent, R borrows the powerful Frisch-Waugh-Lovell Theorem to reduce the computational cost.
Last updated on May 120, 121212
1 min read
How to Explain Bais-Variance Trade-off in a Statistic Way
Bias-Variance Trade-off is usually used to explain accuracy v.s. overfitting tradeoff. However, it is not rigorous and difficult to correlate overfitting with variance. Here is my version of explaining this. Of course, there is not much innovation here and many people could have thought in the same way.
Last updated on May 20, 2022
1 min read
K-Means Clustering is a special version of Gaussian Mixture Models
This article shows why K-means is a special version of Guassian Mixture Model.
Last updated on May 20, 2022
1 min read
What are the assumptions for linear regression and how to solve mis-specification?
A thorough summary of the few assupmtions for Linear Regression and what to do when those assumptions are not met,
Last updated on May 20, 2022
1 min read
What to do when there exists spill-over effect in your ab-testing?
A/B testing is a powerful decision-making tool. However, if social network spill-over effect exists, then the average treatment effect will be underestimated. This is because the control group will also be exposed to some condition of treatment.
Last updated on May 20, 2022
5 min read
Why does the degrees of freedom in Linear Regression equal n-p?
The degree of freedom represents the number of “free” or independent $N(0,1)^2$ in the residuals from linear regression.
Last updated on May 20, 2022
3 min read
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