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1500 questions
42
votes
1 answer
How to determine significant principal components using bootstrapping or Monte Carlo approach?
I am interested in determining the number of significant patterns coming out of a Principal Component Analysis (PCA) or Empirical Orthogonal Function (EOF) Analysis. I am particularly interested in applying this method to climate data. The data…
Marc in the box
- 3,712
42
votes
3 answers
Difference between generalized linear models & generalized linear mixed models
I am wondering what the differences are between mixed and unmixed GLMs. For instance, in SPSS the drop down menu allows users to fit either:
analyze-> generalized linear models-> generalized linear models &
analyze-> mixed models-> generalized…
user9203
- 689
42
votes
3 answers
How to interpret OOB and confusion matrix for random forest?
I got a an R script from someone to run a random forest model. I modified and run it with some employee data. We are trying to predict voluntary separations.
Here is some additional info: this is a classification model were 0 = employee stayed, 1=…
daniellopez46
- 945
42
votes
4 answers
What is the difference between a stationary test and a unit root test?
What is the difference between the Kwiatkowski–Phillips–Schmidt–Shin (KPSS) test and the augmented Dickey-Fuller (ADF) test? Are they testing the same thing? Or do we need to use them in different situations?
Flying pig
- 6,239
42
votes
3 answers
Interpreting residual diagnostic plots for glm models?
I am looking for guidelines on how to interpret residual plots of glm models. Especially poisson, negative binomial, binomial models. What can we expect from these plots when the models are "correct"? (for example, we expect the variance to grow…
Tal Galili
- 21,541
42
votes
5 answers
Good games for learning statistical thinking?
Are there any games that get the player "think like a statistician"?
For example, lightbot gets you to "think like a programmer" (in a very basic way). Are there any games - designed for entertainment or teaching - that can help get one comfortable…
Emile
- 1,097
42
votes
4 answers
Why is max pooling necessary in convolutional neural networks?
Most common convolutional neural networks contains pooling layers to reduce the dimensions of output features. Why couldn't I achieve the same thing by simply increase the stride of the convolutional layer? What makes the pooling layer necessary?
user3667089
- 533
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42
votes
5 answers
Yolo Loss function explanation
I am trying to understand the Yolo v2 loss function:
\begin{align}
&\lambda_{coord} \sum_{i=0}^{S^2}\sum_{j=0}^B \mathbb{1}_{ij}^{obj}[(x_i-\hat{x}_i)^2 + (y_i-\hat{y}_i)^2 ] \\&+ \lambda_{coord} \sum_{i=0}^{S^2}\sum_{j=0}^B…
Kamel BOUYACOUB
- 451
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42
votes
4 answers
Maximum Mean Discrepancy (distance distribution)
I have two data sets (source and target data) which follow different distributions. I am using MMD - that is a non-parametric distribution distance - to compute marginal distribution between the source and target data.
source data, Xs
target data,…
Mahsa
- 521
42
votes
3 answers
How to take derivative of multivariate normal density?
Say I have multivariate normal $N(\mu, \Sigma)$ density. I want to get the second (partial) derivative w.r.t. $\mu$. Not sure how to take derivative of a matrix.
Wiki says take the derivative element by element inside the matrix.
I am working…
user1061210
- 1,085
42
votes
3 answers
Why do naive Bayesian classifiers perform so well?
Naive Bayes classifiers are a popular choice for classification problems. There are many reasons for this, including:
"Zeitgeist" - widespread awareness after the success of spam filters about ten years ago
Easy to write
The classifier model is…
winwaed
- 1,133
42
votes
2 answers
Dropping one of the columns when using one-hot encoding
My understanding is that in machine learning it can be a problem if your dataset has highly correlated features, as they effectively encode the same information.
Recently someone pointed out that when you do one-hot encoding on a categorical…
dasboth
- 728
42
votes
3 answers
Classification/evaluation metrics for highly imbalanced data
I deal with a fraud detection (credit-scoring-like) problem. As such there is a highly imbalanced relation between fraudulent and non-fraudulent observations.
http://blog.revolutionanalytics.com/2016/03/com_class_eval_metrics_r.html provides a great…
Georg Heiler
- 595
42
votes
5 answers
Confidence interval for median
I have to find a 95% C.I. on the median and other percentiles. I don't know how to approach this. I mainly use R as a programming tool.
Dominic Comtois
- 2,129
42
votes
14 answers
Regression to the mean vs gambler's fallacy
On the one hand, I have the regression to the mean and on the other hand I have the gambler´s fallacy.
Gambler’s fallacy is defined by Miller and Sanjurjo (2019) as “the mistaken belief that random sequences have a systematic tendency towards…
Luis P.
- 761