**976 terminology questions.**

I heard someone arguing in a conference that when you use the word "association" it indicates to the result of a chi-square test and when you use the word "relation" it indicates to the result of ...

Does a function in the form $e^x/(1+e^x)$ have a standard name? E.g. $y = a + bx$ is a linear function.

Are measures of association, relationship and correlation the same? Different textbooks uses those words interchangeably and Im wondering if the they are the simply the same...

Suppose I administer an exam consisting of 320 multiple-choice questions (i.e., the answer is either correct or incorrect - there's no partial credit). I grade the exams, and now I want to do an ...

Let $X,Y,\epsilon:\Omega\to \mathbb R$ be random variables. Let's say that $X=\text{sign} (Y) +\epsilon$. Then $X$ is not independent of $Y$. However, we have all the information about $Y$ that we ...

I have read this paper Piece-wise quadratic approximations of arbitrary error functions for fast and robust machine learning
My question is
What does the arbitrary error functions mean?

Ng, A.Y., and Jordan, M.I. (2001). On Discriminative vs. Generative classifiers: A comparison of logistic regression and naive Bayes. Advances in Neural Information Processing Systems, 14, pp. 841-8, ...

I'm asking this out of curiosity.
In the past I have thought of an heuristic as a "quick and dirty" rule not based on data analysis, as opposed to a solution which uses machine learning or ...

If one has to suggest, what is it one would call a given object that is to be estimated?
We already have a generic term "estimator" on the one hand. When the context is clear, usually there is no ...

In my probability class the terms "sums of random variables" is constantly used. However, I'm stuck on what exactly that means?
Are we talking about the sum of a bunch of realizations from a random ...

I have the folowing table:
according to this example, there are 40 observations distributed over 10 stores and 4 weeks of the month. Objective: to make a sample of 90%, 80%, 75% and 50% of the 40 ...

What do the terms "dense" and "sparse" mean in the context of neural networks (NNs)? What is the difference between them? Why are they so called?

In a recent colloquium, the speaker's abstract claimed they were using machine learning. During the talk, the only thing related to machine learning was that they perform linear regression on their ...

A list of discrete event distributions are labeled as either with or without finite support.
https://en.wikipedia.org/wiki/List_of_probability_distributions#Discrete_distributions
What does it mean ...

I have data being grouped into 3 ranges: 80-89%; 90-109% 110-120%
Can I call these 3 Terciles? I believe a tercile is the data split into 3 equal sized groups - is there another term I can use ...

It seems like the definition of supervised learning is a subset of reinforcement learning, with a particular type of reward function that is based on labelled data (as opposed to other information in ...

In machine learning, people talk about objective function, cost function, loss function. Are they just different names of the same thing? When to use them? If they are not always refer to the same ...

What does it mean for a standard normal to have mean 0 and standard deviation 1?
I'm having trouble understanding - what is a "normal variable"?

Regarding GARCH models, many authors use the terms asymmetric effects and leverage effects interchangeably and they left me with a doubt on whether these two terms are synonymous.
I get that, for ...

I want to use deep learning in my project. I went through a couple of papers and a question occurred to me: is there any difference between convolution neural network and deep learning? Are these ...

Is there any difference between stride and subsample in convolutional neural networks?

Factor analysis has several rotation methods, such as varimax, quartimax, equamax, promax, oblimin, etc. I am unable to find any information that relates their names to their actual mathematical or ...

What is the history behind the choice of the name "Adam" as used in Adam: A Method for Stochastic Optimization?

I saw a term describing the feature detectors, i.e. shift invariant. What is that mean?
Paper: 1989 Generalization and Network Design Strategies

This is a general question on normalization of data so that all the variables are within the same range.
Why do we normalize data in pattern classification?
How to normalize time series which is ...

From here (slide 23) and here (page 5, 4th slide) I understand that it is said that PPCA (probabilistic PCA) is rotational invariant. It can be written as follows:
$$\text{PPCA}(X) = [\mu, W, \sigma^...

What is the relation between estimator and estimate?

In the following slide I do not understand the definition of the term embedding.
In the third paragraph, it says it is a mapping from low-dim. to high-dim, but in the last paragraph it suggests that ...

At the end of the PCA algorithm one gets a $D\times d$ matrix $U$ such that $z=U^Tx$ (here $x$ is $D$-dimensional and $z$ is $d$ dimensional with $d\leq D$). In multiple sources on the Web I found ...

I'm using Python Keras package for neural network. This is the link. Is batch_size equals to number of test samples? From ...

Given a distribution $d$ on non-negative numbers and a threshold $t > 0$, I define the "truncated" distribution $d_t$ where
$\left\{
\begin{array}{ll}
d_t(x) = 0 & \mbox{when} \ x ...

In PCA and Factor Analysis, there is the term loadings, which refers to factor loadings (onto the original variable).
Does the term (original) variable loading (onto the latent factor) exist?

What is the difference between the terms "kernel" and "filter" in the context of convolutional neural networks?

I read about "MNIST database" on this Wikipedia page which says "MNIST" stands for "Modified National Institute of Standards and Technology". But I see someone uses "MNIST" as "MNIST database" in ...

Statistics is everywhere; common usage of statistical terms is, however, often unclear.
The terms probability and odds are used interchangeable in lay English despite their well-defined and different ...

I want to introduce the data I have taken from a dynamic dataset (GitHub repos) at 12pm today. I want to say the equivalent of "This is the data as of 12pm Sept 4" but am wondering if there is a ...

Could someone tell me what the term 'persistence' mean in time series analysis? It's regarding econometrics and applied regression.

There is a term of art that I either never learned or forgot, referring to an assumption in the context of estimating probabilities. I cannot find it in a quick search of Wiki on, for example, the ...

Suppose I have some multimodal distribution as shown below.
It has two regions of high probability, highlighted in purple.
And within those regions are smaller peaks, highlighted in green.
Is there ...

What's the differences between stochastic models (process) and statistical model (analysis). As I understand, a stochastic model (process) simply means it involves random variables, which is basically ...

In dimensionality reduction technique such as Principal Component Analysis, LDA etc often the term manifold is used. What is a manifold in non-technical term? If a point $x$ belongs to a sphere whose ...

Whilst I understand the term conceptually, I'm struggling to understand it operationally.
Could anyone help me out by offering an example?
Thanks.

I am trying to understand the use of the term “scale” in the 2008 van der Maaten and Hinton t-sne paper.
I’m not sure I exactly understand what they mean by their use of the term “scale”, for ...

I'am getting familiar with the statistical notion of Divergence. The word "divergence" is also used in physics (or vector analysis, see here http://en.wikipedia.org/wiki/Divergence). As I was more ...

I ask this question out of curiosity
earlier today when i was trying to test for heteroscedasticity in R, i accidentally mistook ...

If we focus on sequence modeling (discrete time and discrete observations), Can I claim Makrov Chain or Hidden Markov Model are simple Recurrent Neural Networks (Because both of them have "time ...

I'm new to the deep learning field and I've a question that I didn't get for it a clear answer or explanation in the course, I understand the tensors and the idea behind batches but I don't really get ...

It occurred to me today that the distribution
$$
f(x)\propto\exp\left(-\frac{|x-\mu|^p}{\beta}\right)
$$
could be viewed as a compromise between the Gaussian and Laplace distributions, for $x\in\...

I am trying to learn about Dynamic Regression models. However, the sources on the topic is (relatively) few compared to other TS topics, and so I cannot really get a grasp of where to start. I really ...

This probably is due to my lack of a reference textbook for statistical modeling of time series, anyway I'm not sure which terms we use to distinguish between two different time series classification ...

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