# Tag Info

### Data Science vs Operations Research

While both Operations Research and Data Science both cover a large amount of topics and areas, I'll try to give my perspective on what I see as the most representative and mainstream parts of each. ...

### any hope for a universal automatic parser?

You might be interested in learning about grammar induction: given a set of examples of strings from a context-free language, there are algorithms to learn a context-free grammar that generates those ...

### Detecting events in time series data

Your first step is to characterize what effect you expect an event to have on your signals. Does it change the mean? Increase the mean? Change the variability? The more you can say about the type ...

### Data Science vs Operations Research

This isn't a full answer, since mhum's is quite good in contrasting the differing aims of OR vs DS. Rather, I want to address this comment of yours: I was wondering if, for example, one could use ...

### What kind of logarithm does $\log$ mean in Wikipedia articles?

It depends entirely on context. In mathematics as a whole, $\log$ usually denotes the natural logarithm (base $\mathrm{e}$). In computer science, the situation isn't as clean because we often ...
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### Computer vision: object detection with labels that are single coordinates

The state of the art in such problems is done these days via deep neural networks. Among others, two popular and recent approaches for solving the problem of detection and localization of objects are ...

### Measuring the information of a document?

Assuming that your data comes from a Markovian source, you can estimate the entropy of the source using an optimal compression algorithm such as Lempel–Ziv, whose theoretical version (without limiting ...

### Gramatical evolution doesn't result on creating good constants

In Grammatical Evolution there are three well known approaches to the problem of constant creation: expression based (the "traditional" approach). This is what you're using (arithmetic operators are ...

### Gramatical evolution doesn't result on creating good constants

It sounds like you're saying that your approach is able to effectively find the shape of the expression, but it takes it a lot longer to find the right constants. One possible approach is to generate ...

### Word Frequency with Ordering in O(n) Complexity

The gathering of occurrence counts is O(n), so the trick is really only finding the top k occurrence counts. A heap is a common way to aggregate the top k values, although other methods can be used (...

### How to generate response variable during machine learning?

No. You can't. You need ground truth. You're asking "if I don't know which claims are fraudulent, can an algorithm somehow determine that for me?" The answer of course is no: the algorithm doesn't ...

### Machine Learning: Identify Patterns in Time-Series Data

Yes, your data is "time-series data", since it's a sequence of measurements of the same variable collected over time. Time-series data can be collected continuously or at discrete intervals. Your ...
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### In Data Mining, what does it mean to be greedy?

I'm not a Data Mining expert, but from what I understand, it means the same thing as it does outside of data mining: to improving the solution in a locally optimal way, rather than one that is ...

### Data Science vs Operations Research

As a strategist, I've had the opportunity to work with both sides of the discipline. In trying to explain what OR and DS are to a qualitative MBA executive, my (overly) simplistic one line ...

### Data Searching from a large data set without reading each element

Say you have $n$ entries, $m$ distinct letters, and the $i$-th letter occurs $k_i$ times. You can find the last occurrence of the $i$-th letter using a variant of binary search: Double your step size ...
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### Why does the BFR (Bradley, Fayyad and Reina) algorithm assume clusters to be normally distributed around its centroid?

Roughly, the algorithm needs to estimate the probability to assign a point the correct cluster. So the algorithm add P to a cluster if it is very unlikely that, after all the points have been ...

### Why is it not always possible to compute the centroid of feature vectors?

A metric space consists of a set $X$ of "points" and a metric $d\colon X \times X \to \mathbb{R}_{\geq 0}$ (giving the "distance" between any two points) which satisfies the following constraints: ...
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### Standardizing Data for Neural Networks

You can distinguish between the following types of data (source, see Level of measurement for something similar): Nominal: You can't calculate with them. They only support checks for identity, e.g. ...
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### Exhaustive list of ways to distribute n objects to k sets

The objects you are interested in enumerating are counted by Stirling numbers of the second kind. In particular, $\genfrac{\{}{\}}{0pt}{}{n}{k}$ is the number of ways to partition a set of size $n$ ...
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### Algorithm to find pronounciation rules

Broadly, I can see two possible approaches: machine learning, or data mining Machine learning You could look into using machine learning to learn a transducer that transforms the input sequence (the ...

### What to do when the information gain on decision trees is 0 for all possible splits?

You should process ALL of the possible splits and hope for information gain somewhere down the line.
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### Expected number of common edges for a given tree with any other tree

Let $T$ be your reference tree (on $n$ vertices), and let $R$ be the random tree. Label the edges of the tree randomly from $1$ to $n-1$. Let $X_i$ denote the event that the $i$th edge of $R$ is an ...
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The short answer is: I don't know. Visualizations There's been lots of work on visualizing the MNIST data set, in 2 dimensions, and even in 3 dimensions. For instance, here's an embedding into 2D ...

### Relation and difference between information retrieval and information extraction?

From a modeling standpoint, information retrieval is a deep field predicated on several disciplines, including statistics, math, linguistics, artificial intelligence and now data science. In practice, ...

### Machine Learning - Support Vector Machines

In addition to listed references, I would recommend the following: A. Nefedov. Support Vector Machines: A Simple Tutorial, 2016 N. Cristianini, J. Shawe-Taylor. An Introduction to Support Vector ...

### How to generate response variable during machine learning?

Let me know of any other methods to generate response variable when there is none Anomaly detection techniques could be what you're looking for (but you don't "generate response variable when there ...

### A decision algorithm to choose what partner to use

Techniques developed for the multi-armed bandit problem might be useful for discovering the partner with the best acceptance rate and dealing with the changing acceptance rate over time. Those ...

### Data Science vs Operations Research

I obtained my Operations Research degree from a military institution and have been using it for military applications for about 15 years. In that timeframe, Data Science has grown into a main-stream ...
### What kind of logarithm does $\log$ mean in Wikipedia articles?
I think it depends on the situation. For a mathematician, $\log n$ probably means the natural logarithm. For a computer scientist, $\log n$ probably denotes the base $2$ logarithm, etc. I think ...