Highest scored questions
218,409 questions
1373
votes
27
answers
973k
views
Making sense of principal component analysis, eigenvectors & eigenvalues
In today's pattern recognition class my professor talked about PCA, eigenvectors and eigenvalues.
I understood the mathematics of it. If I'm asked to find eigenvalues etc. I'll do it correctly like ...
- 14k
826
votes
10
answers
1.2m
views
How to choose the number of hidden layers and nodes in a feedforward neural network?
Is there a standard and accepted method for selecting the number of layers, and the number of nodes in each layer, in a feed-forward neural network? I'm interested in automated ways of building neural ...
- 58.9k
687
votes
12
answers
512k
views
What is the difference between "likelihood" and "probability"?
The wikipedia page claims that likelihood and probability are distinct concepts.
In non-technical parlance, "likelihood" is usually a synonym for "probability," but in statistical usage there is a ...
- 7,741
633
votes
5
answers
527k
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Relationship between SVD and PCA. How to use SVD to perform PCA?
Principal component analysis (PCA) is usually explained via an eigen-decomposition of the covariance matrix. However, it can also be performed via singular value decomposition (SVD) of the data matrix ...
- 108k
576
votes
15
answers
254k
views
What is the intuition behind beta distribution?
Disclaimer: I'm not a statistician but a software engineer. Most of my knowledge in statistics comes from self-education, thus I still have many gaps in understanding concepts that may seem trivial ...
- 10.1k
571
votes
11
answers
670k
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What is the difference between test set and validation set?
I found this confusing when I use the neural network toolbox in Matlab.
It divided the raw data set into three parts:
training set
validation set
test set
I notice in many training or learning ...
- 7,269
565
votes
23
answers
333k
views
Why square the difference instead of taking the absolute value in standard deviation?
In the definition of standard deviation, why do we have to square the difference from the mean to get the mean (E) and take the square root back at the end? Can't we just simply take the absolute ...
- 5,905
500
votes
20
answers
180k
views
The Two Cultures: statistics vs. machine learning?
Last year, I read a blog post from Brendan O'Connor entitled "Statistics vs. Machine Learning, fight!" that discussed some of the differences between the two fields. Andrew Gelman responded ...
447
votes
5
answers
178k
views
How to understand the drawbacks of K-means
K-means is a widely used method in cluster analysis. In my understanding, this method does NOT require ANY assumptions, i.e., give me a dataset and a pre-specified number of clusters, k, and I just ...
- 6,979
443
votes
9
answers
901k
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What is the difference between fixed effect, random effect in mixed effect models?
In simple terms, how would you explain (perhaps with simple examples) the difference between fixed effect, random effect in mixed effect models?
- 6,348
441
votes
13
answers
288k
views
Bayesian and frequentist reasoning in plain English
How would you describe in plain English the characteristics that distinguish Bayesian from Frequentist reasoning?
- 4,519
426
votes
11
answers
190k
views
Explaining to laypeople why bootstrapping works
I recently used bootstrapping to estimate confidence intervals for a project. Someone who doesn't know much about statistics recently asked me to explain why bootstrapping works, i.e., why is it that ...
- 5,289
421
votes
17
answers
175k
views
What happens if the explanatory and response variables are sorted independently before regression?
Suppose we have data set $(X_i,Y_i)$ with $n$ points. We want to perform a linear regression, but first we sort the $X_i$ values and the $Y_i$ values independently of each other, forming data set $(...
- 3,891
418
votes
7
answers
429k
views
When conducting multiple regression, when should you center your predictor variables & when should you standardize them?
In some literature, I have read that a regression with multiple explanatory variables, if in different units, needed to be standardized. (Standardizing consists in subtracting the mean and dividing ...
- 4,591
414
votes
7
answers
1.7m
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How to normalize data to 0-1 range?
I am lost in normalizing, could anyone guide me please.
I have a minimum and maximum values, say -23.89 and 7.54990767, respectively.
If I get a value of 5.6878 how can I scale this value on a scale ...
- 4,595