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1500 questions
91
votes
6 answers

If I have a 58% chance of winning a point, what's the chance of me winning a ping pong game to 21, win by 2?

I have a bet with a co-worker that out of 50 ping pong games (first to win 21 points, win by 2), I will win all 50. So far we've played 15 games and on average I win 58% of the points, plus I've won all the games so far. So we're wondering if I have…
richard
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91
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11 answers

Why should I be Bayesian when my model is wrong?

Edits: I have added a simple example: inference of the mean of the $X_i$. I have also slightly clarified why the credible intervals not matching confidence intervals is bad. I, a fairly devout Bayesian, am in the middle of a crisis of faith of…
Guillaume Dehaene
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91
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2 answers

How to normalize data between -1 and 1?

I have seen the min-max normalization formula but that normalizes values between 0 and 1. How would I normalize my data between -1 and 1? I have both negative and positive values in my data matrix.
covfefe
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91
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3 answers

What is the intuition behind SVD?

I have read about singular value decomposition (SVD). In almost all textbooks it is mentioned that it factorizes the matrix into three matrices with given specification. But what is the intuition behind splitting the matrix in such form? PCA and…
SHASHANK GUPTA
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91
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6 answers

Why is the L2 regularization equivalent to Gaussian prior?

I keep reading this and intuitively I can see this but how does one go from L2 regularization to saying that this is a Gaussian Prior analytically? Same goes for saying L1 is equivalent to a Laplacean prior. Any further references would be great.
Anonymous
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1 answer

How to apply Neural Network to time series forecasting?

I'm new to machine learning, and I have been trying to figure out how to apply neural network to time series forecasting. I have found resource related to my query, but I seem to still be a bit lost. I think a basic explanation without too much…
solartic
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90
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3 answers

An example: LASSO regression using glmnet for binary outcome

I am starting to dabble with the use of glmnet with LASSO Regression where my outcome of interest is dichotomous. I have created a small mock data frame below: age <- c(4, 8, 7, 12, 6, 9, 10, 14, 7) gender <- c(1, 0, 1, 1, 1, 0, 1, 0, 0) bmi_p…
Matt Reichenbach
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90
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26 answers

What is the single most influential book every statistician should read?

If you could go back in time and tell yourself to read a specific book at the beginning of your career as a statistician, which book would it be?
Neil McGuigan
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90
votes
2 answers

ImageNet: what is top-1 and top-5 error rate?

In ImageNet classification papers top-1 and top-5 error rates are important units for measuring the success of some solutions, but what are those error rates? In ImageNet Classification with Deep Convolutional Neural Networks by Krizhevsky et al.…
daniel451
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90
votes
5 answers

What are modern, easily used alternatives to stepwise regression?

I have a dataset with around 30 independent variables and would like to construct a generalized linear model (GLM) to explore the relationship between them and the dependent variable. I am aware that the method I was taught for this situation,…
fmark
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90
votes
4 answers

How to use Pearson correlation correctly with time series

I have 2 time-series (both smooth) that I would like to cross-correlate to see how correlated they are. I intend to use the Pearson correlation coefficient. Is this appropriate? My second question is that I can choose to sample the 2 time-series as…
user1551817
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90
votes
4 answers

What're the differences between PCA and autoencoder?

Both PCA and autoencoder can do demension reduction, so what are the difference between them? In what situation I should use one over another?
RockTheStar
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90
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6 answers

How to tell if data is "clustered" enough for clustering algorithms to produce meaningful results?

How would you know if your (high dimensional) data exhibits enough clustering so that results from kmeans or other clustering algorithm is actually meaningful? For k-means algorithm in particular, how much of a reduction in within-cluster variance…
xuexue
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89
votes
11 answers

What are disadvantages of using the lasso for variable selection for regression?

From what I know, using lasso for variable selection handles the problem of correlated inputs. Also, since it is equivalent to Least Angle Regression, it is not slow computationally. However, many people (for example people I know doing…
xuexue
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89
votes
2 answers

Basic question about Fisher Information matrix and relationship to Hessian and standard errors

Ok, this is a quite basic question, but I am a little bit confused. In my thesis I write: The standard errors can be found by calculating the inverse of the square root of the diagonal elements of the (observed) Fisher Information…
Jen Bohold
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