Questions tagged [terminology]

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

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2
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1answer
42 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
126 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 ...
2
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2answers
45 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
36 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 ...
3
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1answer
42 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 ...
2
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1answer
49 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
29 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
23 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
32 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
44 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 ...
3
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1answer
307 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
31 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
178 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 ...
1
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1answer
33 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
105 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
376 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? ...
0
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1answer
59 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
317 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 ...
7
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3answers
11k 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 ...
3
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1answer
817 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
54 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 ...
6
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1answer
5k 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
4k 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
18k 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 ...
3
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1answer
936 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
522 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
96 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?
2
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1answer
926 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
85 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
133 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: ...
8
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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?
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1answer
688 views

Convolutional Neural Network: learning capacity and image coverage

I was looking through a CNN tutorial and towards the end they refer to learning capacity and image coverage during network learning diagnostics What do those 2 terms mean in the context of a ...
2
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0answers
84 views

What is the scientific term/keyword for “big data time series”?

There are business articles from 2014 and 2015 that the time series analysis of the big data is the next big thing. However Google returns almost no scientific articles under the query "big data time ...
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1answer
64 views

Data that's not missing is called…?

Is there a standard term for data that's not missing? I.e. is it called non-missing, present, or something else? Thanks!
2
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1answer
254 views

Are stacked NN the second generation of NN?

Spiking Neural Networks are said to be the NN's third generation. Feed-Forward NN are the first. What is the second Generation? Stacked NN?
0
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1answer
127 views

What is the term for data that is too sparse to represent the underlying data model?

I am giving a presentation on Data Science, and I want to talk about the idea that data that is not "big" enough is a big barrier for Machiene Learning. Looking online, there are concepts like ...
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2answers
37 views

Analytics term for turning row values into column names and count its assigned values

Do we have a data mining/analysis term for turning row values into column names and count its assigned values?
9
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3answers
296 views

Performance measure: why it is called recall?

precision is the fraction of retrieved instances that are relevant, while recall (also known as sensitivity) is the fraction of relevant instances that are retrieved. I know their meaning but I don'...
0
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1answer
134 views

Looking for a rough explanation of additive hidden nodes and radial basis functions

I'm working on a neural networks project right now and for that I'm reading a bunch of scientific papers, in a few of those the terms additive hidden nodes and radial basis functions are thrown around,...
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1answer
268 views

Term for relative recall

For in calculating success in information retrieval, precision and recall are fairly standard measurements, relating to accuracy of the results, and to what extent the results are comprehensive, ...
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2answers
1k views

Why did Tufte call this a “superbly produced duck”?

I think I understand Tufte's concept of a "Duck" -- A graphic that is taken over by decorative forms. But I couldn't understand why he called this a duck (a "superbly produced" one at that). It ...
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3answers
2k views

Are Word2Vec and Doc2Vec both distributional representation or distributed representation?

I have read that distributional representation is based on distributional hypothesis that words occurring in similar context tends to have similar meanings. Word2Vec and Doc2Vec both are modeled ...
4
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1answer
162 views

In Neural Networks and deep neural networks what does label-dropout mean

If you take the following sentence from an article on deep neural networks to regularize the classifier layer by estimating the marginalized effect of label-dropout during training. What does ...
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3answers
5k views

What is the difference between (objective / error / criterion / cost / loss) function in the context of neural networks?

The title says it all: I have seen three terms for functions so far, that seem to be the same / similar: error function criterion function cost function objective function loss function I was ...
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1answer
106 views

What is a Recurrent Heavy Subgraph?

I recently came across this term recurrent heavy subgraph in a talk. I don't seem to understand what it means and Google doesn't seem to show any good results. Can ...
6
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1answer
2k views

Where does the name 'LSTM' come from?

Long short-term memory is a recurrent neural network architecture introduced in the paper Long short-term memory. Can you please tell me where the name comes from? ("Memory", as the network can ...
3
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2answers
38 views

Term for calculated values that lose pertinence when changing scale

I'm trying to find the term for a type of calculations or values that cannot be simpply added or multiplied when zooming in or out from a temporal scale. I know it's not very clear, if it were I would ...
9
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2answers
3k views

Why is finite precision a problem in machine learning?

Can you explain what is finite precision? Why is finite precision a problem in machine learning?