Questions tagged [terminology]

Indicates questions asking about the use and meaning of specific technical words/concepts in statistics.

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Who invented the concept of over-fitting?

The wikipedia article on overfitting references to Oxford dictionary entry that claims: "Origin 1930s; earliest use found in Quarterly Review of Biology. From over- + fitting." It is ...
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1answer
16 views

Which term is correct Datafication or Datification?

I have recently started reading Introduction to Data Science: A python approach to Concepts, Techniques, and Applications and taking notes on Data Science. Chapter 1 repeatedly uses the term ...
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2answers
69 views

Loss function in GradientBoostingRegressor

I was looking at the Scikit-Learn documentation for GradientBoostingRegressor. Here it says that we can use 'ls' as a loss function which is least squares regression. But i am confused since least ...
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1answer
19 views

Terminology in machine learning: exogenous features vs external features

I am currently writing a scientific paper and do not know whether to call some of my input features of my neural network either external or exogenous. My neural network receives as input features like ...
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16 views

What is the difference between “Document Layout Analysis” / “Document Understanding” / “Document Structure Analysis”

All three terms sound super similar: [...] document layout analysis is the process of identifying and categorizing the regions of interest in the scanned image of a text document. A reading system ...
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1answer
36 views

What's the of all values above some percentile called? How do I get it in pandas?

Let's say I have a list of numbers, and I want the mean of all numbers that are greater than the 95th percentile. Is there some standard term for that value? ("Mean of a histogram bin"? &...
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1answer
20 views

How to distinguish between different values of a hyperparameter in communication?

From Wikipedia: In machine learning, a hyperparameter is a parameter whose value is used to control the learning process. If we go by the definition of parameter in What's the difference between an ...
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2answers
80 views

What is the difference between a “cell” and a “layer” within neural networks?

So I understand what "layers" are. If you have 5 layers in your model, your data basically gets transformed 5 times via 5 activation functions. The number of "neurons" within a ...
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16 views

Is there any research on zonal OCR / field level ORC / template OCR?

I've recently found the term "Zonal OCR": (source 1, 2, 3, 4). It seems to be essentially OCR, but restricted to relevant parts of the document. The interesting task about which I want to ...
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10 views

Fitting Point Set with Other Point Sets [closed]

I'm attempting to recreate some figures from a publication I read (I'm a math minor, so apologies in advance for my weak terminology knowledge, and for the same reason if I'm in the wrong stack site). ...
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1answer
22 views

Terminology Question: Place Coding

While reading the paper "Backpropagation Applied to Handwritten Zip Code Recognition", one of the original papers attributed to the development of convolutional neural networks, on page 3, ...
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0answers
14 views

What is the appropriate approach for training time series data against multiple, consecutive labels?

Let's say we have a time series $\{{\bf x}_i\}$ of features and are trying to learn to predict a time series $\{t_i\}$ using a neural network. Our goal is to be able to predict the time series value $...
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46 views

Time-series data paradigms (snapshot vs transition)

Given a hypothetical scenario of modeling events from a vehicle for the purpose of determining "trips", it seems to me there are two paradigms: capturing state transitions or capturing state snapshots....
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5answers
831 views

What is the difference between explainable and interpretable machine learning?

O’Rourke says that explainable ML uses a black box model and explains it afterwards, whereas interpretable ML uses models that are no black boxes. Christoph Molnar says interpretable ML refers to the ...
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1answer
101 views

How are the channels handled in CNN? Is it independently processed or fused?

Let's assume that we are talking about 2D convolutions applied on images. In a grayscale image, the data is a matrix of dimensions $w \times h$, where $w$ is the width of the image and $h$ is its ...
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1answer
53 views

What is the layer above/below in a NN?

In the lecture notes of CS231n, it says (emphasis mine) ... There are three major sources of memory to keep track of: From the intermediate volume sizes: These are the raw number of ...
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1answer
64 views

Terminology - regression with one output and multiple output variables

I am trying to predict the response when the input is represented by Fourier transform. These form the features and are typically represented as a vector, $x_1,x_2,...,x_d$ where $d$ is the length of ...
2
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1answer
899 views

Ordered and unordered categorical features – terminology

In the famous book "The Elements of Statistical Learning" by Hastie et al., the authors denoted unordered categorical variables as qualitative variables / nominal variables / factors. I wonder, do ...
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1answer
174 views

Regression: What defines Linear and non-linear models or functions

Linear regression is used when there is a linear relationship between the input and output variables. Does this linear relationship mean that there is no power over the variables or the parameters? In ...
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2answers
69 views

About different structures of neural network

https://www.mathworks.com/help/deeplearning/ref/fitnet.html is the tutorial that I am following to understand fitting data to a function. I have few doubts regarding structure and terminologies which ...
2
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1answer
79 views

Conceptual questions on MLP and Perceptrons

I am facing some confusion regarding the terminologies assocaiated to classification and regression problems esp. using the MLP and Perceptron models. These are the following: 1) When the data is ...
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1answer
44 views

What are the points called in a dataset where the points have the same features but different labels

What are the points called in a dataset where the points have the same features but different labels? For example, I am trying to predict whether some object is a hot dog. But I only have access to ...
3
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1answer
944 views

Could anyone explain these terms, “input space”, “feature space”, “sample space”, “hypothesis space”, “parameter space” with a concrete example?

People use these terms "input space", "feature space", "sample space", "hypothesis space", "parameter space" in machine learning. Could anyone explain these terms with a concrete example, such as ...
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2answers
37 views

Is the _error_ in the context of ML always just the difference of predictions and targets?

Simple definitional question: In the context of machine learning, is the error of a model always the difference of predictions $f(x) = \hat{y}$ and targets $y$? Or are there also other definitions of ...
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1answer
26 views

What is the level of measurement / name of the scale of list-features?

If you look at publications, you can have a dataset title of publication list of authors number of pages year of publication The Level of measurement of "number of pages" is interval scale, the ...
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2answers
37 views

What is the standard terminology for the output matrix of a hidden layer in a CNN?

The output of a hidden layer $h_i$ in a convolutional neural network is (generally) a 3D grid of values. These values are the outputs of the neurons of layer $h_i$. Is there a standard way to refer to ...
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2answers
51 views

What's the name of data points that trained model gets on input in production?

I need some machine learning vocabulary advice. What do you call input data that a trained model gets in production? I know that labelled or unlabelled data it gets during training is called ...
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1answer
1k views

Terminology: “flat geometry” in the context of clustering

Sklearn's documentation refers to "flat" or "non-flat" geometry of clusters to describe the use-cases of their implemented clustering algorithms. Those terms are not directly defined. However, the ...
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2answers
212 views

What fits in a Data Description Report/ Data Exploration Report?

So I am trying to get familiar with Crisp-DM and found the terms "Data Description Report" and "Data Exploration Report", which seem oddly vague in their definition. So far I only found this right ...
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3answers
1k views

Is a “curve” considered “linear”?

In linear regression, we are fitting a polynomial to a set of data points. In Bishop's book of Pattern Recognition & Machine Learning, there are a few examples where the fit is a curve or a ...
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1answer
34 views

If this is “big-endian”, then what is this? [closed]

If an ISO 8601 date is “big-endian”, i.e. the most significant bit is first and the least significant is last, then what do we call data structures where the most significant part is first/at the top, ...
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1answer
124 views

What is the difference between market segmentation and customer segmentation?

Market segmentation seems to be the more widespread, both in books and on websites: What are the differences between market segmentation and customer segmentation? Both are basically about clustering ...
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2answers
438 views

Terminology - cross-validation, testing and validation set for classification task

Confusion1) If k=10 then does this mean that 90% is for training and 10% for testing? So always we have k% for testing? ...
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1answer
64 views

Collection of several learners [closed]

I have few questions for which I could not extract answers from text books and online tutorials. Therefore, will be extremely grateful if the following points are clarified. 1) If I want to apply SVM,...
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0answers
381 views

What are towers in inception architecture and tensorflow?

My understanding of towers in inception architecture and in tensorflow terminology is that they are part of a neural network model for which separate computation can happen on forward phase and ...
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3answers
29k views

What does “baseline” mean in the context of machine learning?

What does "baseline" mean in the context of machine learning and data science? Someone wrote me: Hint: An appropriate baseline will give an RMSE of approximately 200. I don't get this. Does he ...
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2answers
2k views

What is the difference between bootstrapping and sampling in reinforcement learning?

I have come across a David Silver's slide which contains both the terms "bootstrapping" and "sampling". Is there any realistic example which helps me to understand the concepts better.
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1answer
63 views

What is an aspect in opinion mining?

It's quite a challenging task of aspect extraction in the field of opinion mining if you look at the number of related papers. But what is an aspect in the field of opinion mining?
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0answers
36 views

Term for Methods of Representing Repeated Text in Classifier

A colleague told me that there are terms for two different methods of representing repeated text in the training set for a classifier, but he could not recall them. What are the terms for the options ...
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1answer
7k views

What is the difference between “expected return” and “expected reward” in the context of RL?

The value of a state $s$ under a certain policy $\pi$, $V^\pi(s)$, is defined as the "expected return" starting from state $s$. More precisely, it is defined as $$ V^\pi(s) = \mathbb{E}\left(R_t \mid ...
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3answers
6k views

What is the difference between outlier detection and anomaly detection?

I would like to know the difference in terms of applications (e.g. which one is credit card fraud detection?) and in terms of used techniques. Example papers which define the task would be welcome.
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2answers
4k views

What is representation learning?

I am reading the Chapter-1 of the Deep Learning book, where the following appears: A wheel has a geometric shape, but its image may be complicated by shadows falling on the wheel, the sun glaring ...
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10answers
21k views

Why are Machine Learning models called black boxes?

I was reading this blog post titled: The Financial World Wants to Open AI’s Black Boxes, where the author repeatedly refer to ML models as "black boxes". A similar terminology has been used at ...
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1answer
1k views

Is there any difference between 'classification' and 'categorization' based on machine learning terminology?

When I was learning about classification models, it came to my mind that if there is any difference between "categories" and "classes" on the basis of machine learning terminology? If there is no ...
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1answer
916 views

What are stovepipes?

I am reading the book The Data Warehouse Lifecycle Toolkit by Ralph Kimball. I come across the term Stovepipes fairly often. After doing some research I read that Stovepipes are when you don't have ...
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1answer
352 views

Is there a term for “this month last year” in a report? [closed]

I'm building a report that has month over month data, but also "this month last year". Is there a better/standard way of describing this?
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1answer
1k views

Definition of 'feature coverage'

I have heard the term 'feature coverage' in machine learning. However I found no relative infomation after I googled this term. Could some one give me a definition of 'feature coverage' and some ...
2
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2answers
96 views

chart x-axis spacing terminology question

In the following hand made charts I show some value for years. In the first chart I've evenly spaced each year. On the second chart I've spaced them relativelly to their actual year value within time (...
2
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1answer
181 views

How is a single element of the training set called?

This question is only about the vocabulary. Do / can you say data item data sample recording sample data point something else when you talk about elements of the training / test set? For example: ...
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1answer
4k views

What is a tower?

In many tensorflow tutorials (example) "towers" are mentioned without a definition. What is meant by that?