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Usage and meaning of specific technical words/concepts in statistics.

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What is the definition of layer in neural network?

What is the precise definition of layer in neural network? Are things like concatenate functions, activations, batch normalizations, skip connections considered as layers?
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2answers
57 views

Is it still called Machine Learning when the model does not learn anymore? And how is that called?

Maybe the question is too theoretical or even philosophical, maybe it's even the wrong SE-community. I am wondering how I would call a model which is no longer trained/maintained with new data. Do I ...
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24 views

Random variable concept and terminology [duplicate]

I am a programmer with little mathematical background who started to study statistics/ML recently. I quickly stumbled upon the random variable term and it was hard for me to understand why in ...
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9 views

One shot learning on the user level?

I've been working on a text classification problem, where for each user, there can be hundreds of documents. There are about 1000 users. I was wondering how do I call the learning type, if I decide ...
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2answers
29 views

Decision Tree in layman terms

How can we describe decision tree in laymen's language and what are the major fields that require this?
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Terminology - The underlying pattern determining the data?

A few months ago, I learned a great term for machine learning that describes the "underlying pattern determining the data", as in the true mathematical pattern whether in nature or wherever the data ...
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Is “bootstrapping” in statistics the same as “bootstrapping” in machine learning?

In this article on temporal difference learning (TDL), there is a link to bootstrapping. However, the bootstrapping article seems to focus on quite different things, and I find it hard to see the ...
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Is there an informative term for calling the random elements conditional on which a PDF of a random element is defined?

Let $X_{1}, \dots, X_{n}$ be i.i.d. random elements; suppose the conditional PDF $f_{X_{1} \mid X_{2} , \dots, X_{n}}$ exists. Then I wonder if there is already in literature an informative name for $...
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Random variable or sample space element?

The most common definition of a random variable goes something like "A random variable is a mapping $X:\Omega\to \mathbb{R}$ that assigns a real number $X(\omega)$ to each outcome $\omega$". So a ...
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33 views

Association, relationship and correlation

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...
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363 views

Does the function $e^x/(1+e^x)$ have a standard name?

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

$X$ independent of $Y$ conditional on $Y$ in some subset of the domain?

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 ...
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1answer
31 views

An arbitrary error function

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?
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1answer
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A generic terminology for a given object to be estimated?

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 ...
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1answer
53 views

what type of sample is this?

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 ...
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3answers
51 views

Standard normal intuitive understanding

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"?
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Asymmetry effect vs leverage effect

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 ...
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2answers
69 views

ELI5: What is a Discrete Distribution with finite support?

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 ...
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1answer
960 views

Is supervised learning a subset of reinforcement learning?

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 ...
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Rotational invariance of PPCA

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^...
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Is there a name for the following “truncated” distributions?

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 ...
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1answer
57 views

Factor-loadings vs Variable-loadings

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?
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2answers
38 views

What exactly is called “embedding” in dimensionality reduction?

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 ...
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What does the word “MNIST” stand for “MNIST database”? [closed]

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 ...
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1answer
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Term for one snapshot of dynamic data

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 ...
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1answer
32 views

Technical term for an assumption about probabilities?

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 ...
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In a distribution what do I call regions with high probability mass, that contain smaller peaks within them?

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 ...
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1answer
41 views

Layman's explanation on stochastic and statistical models

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 ...
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0answers
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optimizers in deep learning [duplicate]

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 ...
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20 views

Confusion over terminology for time series classification

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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48 views

Are Bias-Variance trade-off and Mean Squared Prediction Error (MSPE) the same?

I was reading about the Bias-Variance trade-off in the textbook "Elements of statistical learning". Is the expected forecast error listed there the same as the MSPE?
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What exactly should be called “projection matrix” in the context of PCA?

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 ...
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1answer
30 views

Clarification on “intercept”?

I'm currently reading "Competition-Based Dynamic Pricing in Online Retailing: A Methodology Validated" by Fisher, Gallino, and Li. In the paper they mentioned that variables $\alpha_j$ and $\alpha_r$ ...
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Exogenous Switching Treatment Regression

Can anyone explain what this term means? I was reading the paper "What Determines Gender Inequality in Household Food Security in Kenya? Application of Exogenous Switching Treatment Regression" https:/...
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1answer
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What's the definition of “Dynamic Regression Models”?

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 ...
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Difference between Beta process and Beta regression?

In a layman language, how the difference can be defined between statistical process and the same named GLM such as poisson processes and poisson regression or beta processes and beta regression? How ...
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1answer
75 views

Meaning of “Logistic regression and Cox proportional hazards regression models were multivariable adjusted for age, gender ..” etc

From the abstract to the study titled "Association between the antioxidant uric acid and depression and antidepressant medication use in 96 989 individuals": We examined plasma levels of the ...
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“Liberal” p-values?

My question is rather semantic. When a method routinely produces high p-values it is called conservative. Would you call the opposite, i.e. a method with a high type-II-error rate liberal?
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1answer
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What does this paper mean by mean square error?

I'm reading a paper about estimating fetal weight by ultrasound and other techniques. In Table 2 they give descriptive statistics, to wit: of all the examiners, the one with the highest mean square ...
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2answers
237 views

Notation in statistics (parameter/estimator/estimate)

In statistics, it is very important to differentiate between the following three concepts which are often confused and mixed by students. Usually, books denote by $\theta$ an unknown parameter. Then ...
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1answer
50 views

Is there a known name / keyword to describe continuous manual improvement of the labels used to train a classifier?

It may seem like a very basic question to the machine-learning fellows out there... but: I'm writing a paper on a computer-vision algorithm that identifies various events in time-lapse images of ...
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0answers
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Complement of a confidence set: standard name?

In the context of statistical inference, is there a standard name for the complement of a confidence set? For example, suppose $X$ captures the observed data, $\theta$ the parameter of interest, $\...
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1answer
153 views

How is the family of distributions with PDF proportional to $(1+ax^2)^{-1/a}$ called?

Consider a family of distributions with PDF (up to a proportionality constant) given by $$p(x)\sim \frac{1}{(1+\alpha x^2)^{1/\alpha}}.$$ How is it called? If it does not have a name, how would you ...
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1answer
33 views

Using term “evaluate” instead of “estimate”?

Is it ok or mistake to use this words as synonyms? (E.g. to write "we evaluate variance of the estimator by theorem 1" when I mean that we estimate this variance)?
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1answer
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Proper names for data - quantile and rank

Say I have data from a sample of 100 experiments. For a variable, I'm interested in showing the value x with 0.9 probability of non-exceedance, which is equivalent ...
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2answers
84 views

Does generative model have to be machine learning-based?

According to Wikipedia, Given an observable variable X and a target variable Y, a generative model is a statistical model of the joint probability distribution on X × Y, P(X,Y) However, as far as ...
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2answers
79 views

Can I claim Makrov Chain or Hidden Markov Model are simple Recurrent Neural Networks?

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 ...
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1answer
29 views

Autoregressive vs integrated time series model

An autoregressive series is of the form $$ X_t = c + \varphi_1 X_{t-1} + \varphi_2 X_{t-2} + \cdots + \varepsilon_t $$ An integrated series is of the form $$ (1-B)^d X_t = \varepsilon_t $$ ...
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1answer
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How do we call when one model is trained by another?

Suppose I have one model (say, for image classification) as black box. I don't posess it and don't know it's parameters. Suppose it is web API. Then I take bunch of images, classify them by this ...
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In Regression Analysis, why do we call independent variables “independent”?

I mean some of those variables are strongly correlated among themselves. How / why / in what context do we define them as independent variables?