User user6703592

9 votes

2 answers

891 views

Interview question of biased coin

probability

asked Oct 4, 2020 at 13:43

5 votes

1 answer

284 views

heavier tails means that it is less sensitive to outlying data for logistic and probit

asked May 29 at 16:46

4 votes

1 answer

91 views

one dimension PLS

partial-least-squares

asked Jun 24, 2021 at 16:11

4 votes

1 answer

82 views

The last step of PLSR

regression partial-least-squares

asked Jun 28, 2021 at 8:11

4 votes

1 answer

69 views

how to generate state and reward in model free reinforcement Learning

reinforcement-learning

asked Oct 12, 2020 at 20:23

4 votes

1 answer

92 views

Multiple dim responding variable the relation between CCA and trivial linear regression (PLSR, CCA, PCA, PCR and Linear Regression)

regression pca partial-least-squares

asked Oct 16, 2020 at 19:22

4 votes

1 answer

212 views

F-test: How to use type I error to compute type II error?

hypothesis-testing statistical-significance

asked Mar 2, 2021 at 14:09

4 votes

1 answer

166 views

Why do we need Forward Selection, Forward Stagewise and LARS for solve linear regression

regression

asked Apr 14, 2021 at 9:16

3 votes

1 answer

320 views

What's the loss function of neutral network with a vector output?

machine-learning

asked Feb 24, 2021 at 17:47

3 votes

1 answer

82 views

interview questIon: what's the bias of y = $a(x+\epsilon) + b$ linear regression

regression

asked Oct 17, 2021 at 18:52

2 votes

1 answer

44 views

If a feature has already split, will it hardly be selected to split again in the subsequent tree in a Gradient Boosting Tree

boosting

asked Nov 4, 2021 at 19:01

2 votes

2 answers

174 views

How to detect and remove the duplicate samples

regression machine-learning

asked Jun 30, 2021 at 7:25

2 votes

0 answers

234 views

How does LSTM/RNN deal with the correlated samples and the samples with different lengths

machine-learning lstm

asked Jul 2, 2021 at 4:10

2 votes

1 answer

113 views

How to understand the scaling in Metropolis Hastings MCMC

simulation markov-chain-montecarlo metropolis-hastings mcmc-acceptance-rate

asked Jul 19, 2021 at 11:58

2 votes

1 answer

66 views

Numerically PCA implements SVD or SVD implements PCA

pca svd numerics

asked Jun 12, 2021 at 6:35

2 votes

2 answers

310 views

How to deal with the problem of correlated samples from time series in machine learning

machine-learning time-series

asked Jun 24, 2021 at 5:31

2 votes

0 answers

53 views

Compare the MSE between LASSO and OLS

lasso ridge-regression

asked Aug 17, 2021 at 12:57

2 votes

1 answer

1k views

why does Batch Normalization not work for RNN

recurrent-neural-network

asked Apr 6, 2021 at 6:36

2 votes

1 answer

42 views

How does normalization of samples make the contour line of parameter be ball?

machine-learning

asked Mar 24, 2021 at 19:43

2 votes

1 answer

69 views

probability interview questions of posterior probability of two unfair coins

probability

asked Nov 21, 2020 at 16:42

2 votes

1 answer

726 views

How does PLSR solve Multicollinearity

multicollinearity partial-least-squares

asked Oct 16, 2020 at 9:14

2 votes

1 answer

78 views

should GBDT use the same loss functions for each weak learner

machine-learning boosting

asked Feb 14, 2021 at 6:30

1 vote

0 answers

60 views

interview question use uniformly distribution {1,2,3,4,5} to generate {1,2,3,4,5,6,7} [duplicate]

probability

asked Nov 17, 2020 at 16:36

1 vote

0 answers

258 views

Does LDA need normality assumption for its dimensionality reduction?

normality-assumption discriminant-analysis

asked Dec 17, 2020 at 20:54

1 vote

2 answers

585 views

In Batch Normalization we normalize the test input every layers or only the first layer

machine-learning batch-normalization

asked Mar 25, 2021 at 15:17

1 vote

1 answer

62 views

Adaboost + SVM vs GBM + hange function of SVM

machine-learning svm

asked Mar 31, 2021 at 18:58

1 vote

0 answers

229 views

the $\beta$ and $R^2$ of combination of two simple linear regression

multiple-regression

asked Oct 6, 2020 at 9:59

1 vote

1 answer

2k views

vanishing gradient and gradient zero

machine-learning neural-networks gradient-descent backpropagation

asked Sep 30, 2020 at 5:42

1 vote

0 answers

36 views

Why the prior distribution can be neglected compared with likelihood function in the posterior distribution when sample is large

bayesian

asked Nov 10, 2019 at 18:41

1 vote

0 answers

444 views

limiting variance and asymptotic variance of the inverse sample mean

variance inference asymptotics

asked Feb 16, 2020 at 14:45

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67 Questions

Interview question of biased coin

heavier tails means that it is less sensitive to outlying data for logistic and probit

one dimension PLS

The last step of PLSR

how to generate state and reward in model free reinforcement Learning

Multiple dim responding variable the relation between CCA and trivial linear regression (PLSR, CCA, PCA, PCR and Linear Regression)

F-test: How to use type I error to compute type II error?

Why do we need Forward Selection, Forward Stagewise and LARS for solve linear regression

What's the loss function of neutral network with a vector output?

interview questIon: what's the bias of y = $a(x+\epsilon) + b$ linear regression

If a feature has already split, will it hardly be selected to split again in the subsequent tree in a Gradient Boosting Tree

How to detect and remove the duplicate samples

How does LSTM/RNN deal with the correlated samples and the samples with different lengths

How to understand the scaling in Metropolis Hastings MCMC

Numerically PCA implements SVD or SVD implements PCA

How to deal with the problem of correlated samples from time series in machine learning

Compare the MSE between LASSO and OLS

why does Batch Normalization not work for RNN

How does normalization of samples make the contour line of parameter be ball?

probability interview questions of posterior probability of two unfair coins

How does PLSR solve Multicollinearity

should GBDT use the same loss functions for each weak learner

interview question use uniformly distribution {1,2,3,4,5} to generate {1,2,3,4,5,6,7} [duplicate]

Does LDA need normality assumption for its dimensionality reduction?

In Batch Normalization we normalize the test input every layers or only the first layer

Adaboost + SVM vs GBM + hange function of SVM

the $\beta$ and $R^2$ of combination of two simple linear regression

vanishing gradient and gradient zero

Why the prior distribution can be neglected compared with likelihood function in the posterior distribution when sample is large

limiting variance and asymptotic variance of the inverse sample mean