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Questions tagged [definitions]

a discussion (meta) tag used when there exists *disagreement* or *confusion* about the everyday meaning of a term or phrase.

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Product name matching - Entity Resolution or Entity Linkage or both?

Context I am at the start of a project where I would like to map/match/link external product names to the respective internal product names. The goal should be to ingest related external information (...
Elodin's user avatar
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1 vote
0 answers
15 views

confusion with Xavier Initiliazation definition

When researching online, I keep finding that Xavier/Glorot initialization is: however, the original paper by Glorot said that this was a common initialization strategy that they soon found did not ...
tom394's user avatar
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2 votes
2 answers
395 views

How would you explain Data Science to someone in simple layman terms?

Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from noisy, structured and unstructured data, and apply ...
Pluviophile's user avatar
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1 vote
0 answers
24 views

Definition adjectives for clustering

For a school project, I need to explain which clustering algorithm of Scikit-Learn we need to use based on the input data. The documentation is very well done, especially thanks to a comparative table ...
Kate P's user avatar
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3 votes
1 answer
126 views

Origin of the Boolean Model of Information Retrieval

Simple question, but I can't really find the answer to that: Who "invented" Boolean Retrieval? Of course, I assume that the concept grew over time, but is there a paper or publication that ...
TiMauzi's user avatar
  • 81
-2 votes
1 answer
66 views

When are two neural networks independent from each other? [closed]

I want to know how you would define the independence of a neural network.
user112820's user avatar
1 vote
1 answer
36 views

Intuitive explanation of Adversarial machine learning

How would you explain Adversarial machine learning in simple layman terms for a non-STEM person? What are the main ideas behind Adversarial machine learning?
Pluviophile's user avatar
  • 3,958
0 votes
2 answers
211 views

What is difference between Standard Normal Distribution and Mean Normalization approaches to feature-scaling?

The tag feature-scaling seems to convey that one of the scaling methods is Standard Normal Distribution. Further, I read an Answer on this site saying that Mean Normalization is a form of feature ...
Subhash C. Davar's user avatar
2 votes
1 answer
2k views

What does anneal mean in the context of machine learning?

An article released by Open AI gives an overview of how Open AI Five works. There is a paragraph in the article stating: Our agent is trained to maximize the exponentially decayed sum of future ...
Reuben Walker's user avatar
3 votes
2 answers
186 views

Is it correct to define the F-measure as the harmonic mean of specificity and sensitivity in such a way?

It is common to define the F-measure as a function of precision and recall, as mentioned in [1]: $F_{\beta}=\frac{(1+\beta^2)PR}{\beta^2 P+R}$ However I came across some other cases, another ...
Qubit's user avatar
  • 33
1 vote
1 answer
169 views

Is the search for a specific n-gram the same like a string search?

Is the result of a search for a specific n-gram like sherlock+holmes equal to the result of a regex search for "sherlock holmes" in the same document corpus? So if i read about n-grams for certain ...
bartman99's user avatar
5 votes
2 answers
11k views

What does it mean when we say an algorithm/metric is agnostic

Problem I have all kinds of machine learning terms that co-occur with the word "agnostic", including model-agnostic learning, model-agnostic metric. From the dictionary, it explains the word "...
Mr.Robot's user avatar
1 vote
2 answers
54 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 ...
lo tolmencre's user avatar
0 votes
1 answer
272 views

What is the difference between the value -99 and NaN in a data column?

I am new to data science. I was looking into some datasets and I saw some values like -99, which I discovered later that it means that there is a missing value. Does this mean the same thing as NaN? ...
panchester's user avatar
0 votes
2 answers
840 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 ...
user3839833's user avatar
4 votes
3 answers
7k views

What's The Difference Between The Terms Predictor And Feature

For the term 'predictor', I found the following definition: Predictor Variable: One or more variables that are used to determine or predict the target variable. Whereas Wikipedia contains the ...
r1d1's user avatar
  • 217
6 votes
3 answers
984 views

What is the meaning of the term "pipeline" within data science?

People often refer to pipelines when talking about models, data and even layers in a neural network. What can be meant by a pipeline?
n1k31t4's user avatar
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0 votes
3 answers
1k views

Forecast vs Prediction: What is the difference?

I use the two terms as follows: A prediction model gets features (which can be a time series) as input and gives a fixed-length output (might be multiple values, but "atomic" in some sense) Examples:...
Martin Thoma's user avatar
1 vote
1 answer
360 views

What does the term "proportional to" mean in Bayes Equation?

I don't have a background in maths so I sometimes get confused by basic definitions. Let's for instance consider Bayes Theorem in Bayes Data Analysis: $P(\theta|\textbf{y}) \propto P(\theta) P(\...
aber's user avatar
  • 11
0 votes
1 answer
65 views

Formal definition for parameter setting in data mining context

While reading this material on decision trees, I came across the following statement: The construction of decision tree classifiers does not require any domain knowledge or parameter setting, and ...
hanugm's user avatar
  • 157
1 vote
2 answers
210 views

What is the relationship between AI and data science?

I think they share a lot (e.g. machine learning is a subset of both, right?), but maybe both have elements the other doesn't have? Could you name some in that case? Or is one a subset of the other? ...
13 votes
4 answers
9k 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.
Martin Thoma's user avatar
0 votes
1 answer
499 views

Can the learning rate be considered both a parameter AND a hyper-parameter?

Here is my understanding of those 2 terms: Hyper-parameter: A variable that is set by a human before the training process starts. Examples are the number of hidden-layers in a Neural Network, the ...
Bitcoin Cash - ADA enthusiast's user avatar
5 votes
2 answers
1k views

Difference between Data Engineer and Data Scientist

I'm very confuse with the term Data Engineer and Data Scientist. There are lot of jobs available for both roles in current market with almost same technical skills requirement. Are they same or ...
Ravi's user avatar
  • 151
4 votes
2 answers
4k views

What is the definition of precision for no positive classifications?

The precision is defined as $$\text{precision} = \frac{\text{true positive}}{\text{true positive} + \text{false positive}}$$ Is there any definition what this value should be if there is no ...
Martin Thoma's user avatar
7 votes
2 answers
5k 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?
GeorgeOfTheRF's user avatar
9 votes
1 answer
613 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 "...
Seyed Mohammad's user avatar
6 votes
3 answers
304 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 ...
Benjamin B.'s user avatar
1 vote
2 answers
249 views

What is the definition of knowledge within data science? [closed]

"Knowledge" is crucial within several fields like Knowledge Discovery, Knowledge Distraction, Natural Language Processing, Data Mining, Big Data, etc etc etc. What is the definition of knowledge ...
Berit Larsen's user avatar
7 votes
5 answers
4k views

How is Data Science related to Machine learning?

I went through this comparison of analytic disciplines and this perspective of machine learning, but I am not finding any answers on the following: How is Data Science related to Machine learning? ...
3 votes
1 answer
446 views

What is "data science"? [closed]

In recent years, the term "data" seems to have become a term widely used without specific definition. Everyone seems to use the phrase. Even people as technology-impaired as my grandparents use the ...
Stan Shunpike's user avatar
1 vote
1 answer
66 views

How is the concept of data different for different disciplines?

How is the concept of data different for different disciplines? Obviously, for physicists and sociologists, "data" is something different.
Teusz's user avatar
  • 111
4 votes
1 answer
90 views

What's the difference between data products and intelligent systems?

Basically, both are software systems that are based on data and algorithms.
user3643160's user avatar
24 votes
3 answers
7k views

Starting my career as Data Scientist, is Software Engineering experience required? [closed]

I am an MSc student at the University of Edinburgh, specialized in machine learning and natural language processing. I had some practical courses focused on data mining, and others dealing with ...
cpumar's user avatar
  • 807
6 votes
1 answer
102 views

How to define a custom resampling methodology

I'm using an experimental design to test the robustness of different classification methods, and now I'm searching for the correct definition of such design. I'm creating different subsets of the ...
gc5's user avatar
  • 879
4 votes
1 answer
755 views

Network structure: k-cliques vs. p-cliques

In network structure, what is the difference between k-cliques and p-cliques, can anyone give a brief explaination with examples? Thanks in advanced! ============================ EDIT: I found an ...
user3663635's user avatar
11 votes
3 answers
2k views

Data Science oriented dataset/research question for Statistics MSc thesis

I'd like to explore 'data science'. The term seems a little vague to me, but I expect it to require: machine learning (rather than traditional statistics); a large enough dataset that you have to run ...
user3279453's user avatar
16 votes
3 answers
2k views

Parallel and distributed computing

What is(are) the difference(s) between parallel and distributed computing? When it comes to scalability and efficiency, it is very common to see solutions dealing with computations in clusters of ...
Rubens's user avatar
  • 4,117
26 votes
4 answers
2k views

Is Data Science the Same as Data Mining?

I am sure data science as will be discussed in this forum has several synonyms or at least related fields where large data is analyzed. My particular question is in regards to Data Mining. I took a ...
demongolem's user avatar