Indicates questions asking about the use and meaning of specific technical words/concepts in statistics.
Questions tagged [terminology]
100 questions
42
votes
9 answers
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 several places when referring to ML models. Why is it…
Dawny33
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28
votes
3 answers
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 mean that if my predictive model on the training data…
Meiiso
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20
votes
5 answers
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 degree to which a human can understand the cause…
Funkwecker
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14
votes
4 answers
Performance measure: Why is it called recall and sensitivity?
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't know why it is called recall? I am not a…
Ahmad
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13
votes
4 answers
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.
Martin Thoma
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13
votes
4 answers
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 working on classification problems
$$E(W) = \frac{1}{2}…
Martin Thoma
- 18,630
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12
votes
2 answers
What is a tower?
In many tensorflow tutorials (example) "towers" are mentioned without a definition. What is meant by that?
Benedikt S. Vogler
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10
votes
1 answer
What is the difference between "expected return" and "expected reward" in the context of RL?
The value of a state $s$ under a certain policy $\pi$, $V^\pi(s)$, is defined as the "expected return" starting from state $s$. More precisely, it is defined as
$$
V^\pi(s) = \mathbb{E}\left(R_t \mid s_t = s \right)
$$
where $R_t$ can be defined…
user10640
10
votes
3 answers
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 according to this hypothesis. But, in the original…
chmodsss
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9
votes
1 answer
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 store information because of the recurrence - but where…
Martin Thoma
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9
votes
1 answer
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 "Business Intelligence" mean: "Acting smart &…
Seyed Mohammad
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9
votes
2 answers
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 seemed to me more functional than decorative.…
thanks_in_advance
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8
votes
1 answer
Who invented the concept of over-fitting?
I list the references that I found so far.
Shortly, the first appearance of the term was in 1670, first appearance in in close meaning was in 1827, first appearance in a biological paper was in 1923 and first appearance in statistics was in…
DaL
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8
votes
4 answers
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 affects future instances, what is that called? …
jsmith54
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8
votes
3 answers
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 straight line. I am a bit confused if a curve is linear or…
Srishti M
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