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Questions tagged [terminology]

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

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2answers
115 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
46 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,...
2
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0answers
96 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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0answers
30 views

What is the difference between data mining and unsupervised learning?

In the Wikipedia article about data mining it is written Data mining is the process of discovering patterns in large data sets In the MathWorks article "Machine learning technique for finding ...
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0answers
18 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?
2
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0answers
30 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 ...
4
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1answer
1k 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 ...
5
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2answers
1k 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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0answers
32 views

describing different parts of data

Given a dataset : 20,20,20,20,20,40,50,90,50,40,20,20,20,20,20,20,20 or 21,22,20,19,18,40,50,90,50,40,21,22,18,22,18,22,18 ...
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2answers
3k 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 ...
36
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10answers
14k 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 ...
4
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1answer
533 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
197 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 ...
1
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1answer
52 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
549 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 ...
1
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2answers
72 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 (...
3
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1answer
108 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: ...
5
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1answer
2k 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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0answers
50 views

The term for a situation where the target variable is measured on different scales for different observations

Assume we have two oracles which can take some observation and output a label representing some attribute of the observation, lets say the feature is "quality". Being oracles, their labels are always ...
1
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1answer
515 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
75 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 ...
1
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1answer
61 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
223 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
93 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
35 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
172 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
97 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
174 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, ...
9
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2answers
670 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 ...
8
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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
124 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 ...
4
votes
1answer
3k 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 ...
4
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1answer
96 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 ...
4
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1answer
1k 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
36 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 ...
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5answers
3k views

Is there a difference between “classification” and “labeling”?

Until recently, I thought that "labeling" and "classification" are synonyms. But when I started another question about terminology in computer vision I thought about it: Is there a difference between "...
0
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1answer
41 views

term for data that compares a day to same day of a week/month/year ago

What is the technical term for a report or dataset that compares data of an interval of time with that of the same interval in a previous week, month, or year?
8
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1answer
311 views

Original Meaning of “Intelligence” in “Business Intelligence”

What does the term "Intelligence" originally stand for in "Business Intelligence" ? Does it mean as used in "Artificial Intelligence" or as used in "Intelligence Agency" ? In other words, does "...
6
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3answers
158 views

What is an alternative name for “Unstructured Data”?

I'm writing my thesis at the moment, and for some time - due to a lack of a proper alternative - I've stuck with "unstructured data" for referring to natural, free flowing text, e.g. Wikipedia ...
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1answer
141 views

Is it ethical to claim experience with big data when the data isn't a part of the new advertising/social media/retail fad?

Obviously most employers, when hiring a data scientist, would prefer experience with big data and/or data science. But what can one safely assume they will acknowledge as experience? Let's say ...
8
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4answers
252 views

What is the term for when a model acts on the thing being modeled and thus changes the concept?

I'm trying to see if there is a conventional term for this concept to help me in my literature research and writing. When a machine learning model causes an action to be taken in the real world that ...
0
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1answer
173 views

Canonical VS Graph Isomorphism [closed]

I'm having a having a hard time understanding the difference between an isomorphism in graphs and canonical graphs. I have read through the Wikipedia articles, but it still isn't clicking. Can ...