Using the techniques of artificial intelligence and machine learning to extract patterns from large data sets and transforming those data into a useful, organized form for future processing.

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3
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0answers
18 views

ML with time-series data. Am I doing this right?

I work in renewable energy. My company gathers a lot of data from equipment. This typically includes process data (such as transformer temperature, line voltages, currents, etc.) and discrete alarms ...
1
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0answers
25 views

Inductive Bias - Decision Tree Pruning as a Bias

I am trying to understand inductive bias and have been looking around to try and work it out. I found this which explains what it is briefly but I have struggled to find examples I understand which ...
2
votes
0answers
32 views

two ways of calculating the entropy in attribute selection (decision tree)

The definition of the entropy is $$H(Y) = -\sum p(y_j)\log_2 p(y_j)\,.$$ Now my text book says to compute the entropy for each attribute we consider the grouping of the data by that attribute now ...
3
votes
1answer
48 views

In Data Mining, what does it mean to be greedy?

I am looking at a number of algorithms in Data Mining and some are described as being greedy. My issue is that they seem to be using the term greedy in different ways, which seems contradictory. For ...
3
votes
1answer
57 views

Standardizing Data for Neural Networks

Let's say we have a data set with following features [age, sex, country, city, annual income] [35, male, USA, New York, 73000]. I came across the article which ...
0
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0answers
16 views

Most impactful factor in the given set of values

My question is somewhat similar to this question Need an algorithm to find the input factors that are most affecting the output but the answers does not solve my problem. My question is: I am ...
1
vote
1answer
27 views

Exhaustive list of ways to distribute n objects to k sets

I am working on a research paper and we are developing a brute force algorithm to examine another clustering technique. In this brute force algorithm we test every possible clustering example and see ...
3
votes
1answer
73 views

Algorithm to find pronounciation rules

Suppose that you have a large dictionary with spellings and pronounciations of foreign words, and you want to find a set of pronunciation rules. They should have the simplest form: a sequence of ...
0
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0answers
27 views

What are some data mining algoritms used in finance?

I want to test the applicability of homomorphic encryption in the financial domain, as suggested in Can homomorphic encryption be practical ?. Now, I want to know what algorithms are used for ...
0
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2answers
29 views

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

I just started studying decisions trees and I am trying to construct a tree for a training set which uses Status as the class label. I am using the misclassification error as measure of impurity. ...
4
votes
1answer
39 views

Expected number of common edges for a given tree with any other tree

So I am working on a problem where I have a set of (labeled) nodes and I have a tree structure (rooted) over that set of nodes. The goal for me is to automatically generate that tree structure. To ...
1
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0answers
36 views

Text data comparison

Okay lets say i have two data structures . two phone data for example containing their Name and spec ( cpu , ram , display etc ) . I want to check if these two phones are the same or not . Their names ...
1
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1answer
35 views

How to identify labels in unsupervised learning?

Let's say I am working on handwritten digit recognition (0 to 9). I know for instance that if I use clustering then I need to look for 10 clusters. But once I have the 10 clusters,how do I identify ...
0
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0answers
22 views

Apriori vs Associative Mining

From what I know the Apriori mining algorithm falls under the category of associative mining, meaning it extracts information using rules based on relationships in the data. When I do research on both ...
0
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2answers
77 views

Transforming training data for machine learning algorithms

If you want to make good predictions with machine learning (supervised learning in particular), you need a good training set. And relevant predictors in your feature set can be overshadowed by ...
0
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0answers
19 views

what is the best theory/model to use for prediction in multivariate data?

I use a software for pollutant propagation on rivers that takes as input a set of parameters (p1, p2, ...pn) and creates an output file which is basically a matrix where on each row there is ...
8
votes
0answers
75 views

What are some efficient ways to find the differences between two large corpuses of text that have similar, but differently ordered content?

I have two large files containing paragraphs of English text: The first text is about 200 pages long and has about 10 paragraphs per page (each paragraph is 5 sentences long). The second text ...
0
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0answers
160 views

Most frequently auto-tagging algorithms for text documents

Please if it's possible introduce the newest and most frequently auto-tagging algorithms for auto-tag text document. I want to get one text document and export tag for that. I also saw TF-IDF but it ...
0
votes
1answer
43 views

Definition and properties of support

From Xiong, Hui, Shashi Shekhar, Pang-Ning Tan, and Vipin Kumar. “TAPER: A Two-Step Approach for All-Strong-Pairs Correlation Query in Large Databases.” Knowledge and Data Engineering, IEEE ...
2
votes
2answers
85 views

Can you get O(n) with a word frequency algorithm?

By a word frequency algorithm: An algorithm gets a document as an input, and returns each unique word along with the number of times it has appeared in the document. For example: in:"Hello my name ...
0
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0answers
31 views

Adjust FCM algorithm with size constrains

I want to cluster a list of property addressed based on distance and limit the size of each cluster. The properties are currently assigned to modules by discretion of managers. But I hope to develop ...
1
vote
1answer
57 views

Adding concept drift to data sets

I'm about to work with concept drift problem in data streams. I need to start with real data sets from UCI machine learning repository and add to them concept drift (in attributes domain). Do you ...
2
votes
1answer
62 views

Most frequently tools or programming language for implementation text processing and nlp algorithms in academic papers and journals [closed]

I want to prototype and try some idea (some algorithm) in the field of text processing and nlp and if the results was good I want to publish some paper or journal article about that. I am familiar ...
2
votes
1answer
52 views

Looking for a paper comparing NLP methods with Data Mining techniques

I've recently attended a conference, where one of the participants mentioned a recent paper published by a Google employee, which showed that using data mining techniques in application to NLP might ...
1
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0answers
65 views

Formula for number of parameters in an undirected graphical (probability) model

I have googled endlessly, and I cannot find it. Can anyone point me to a reference that gives a way to calculate the number of parameters in an undirected Graphical Model? Adapting from the similar ...
0
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0answers
19 views

Is this an accepted/valid clustering evaluation metric?

We have a clustering algorithm where the number of clusters isn't known to the algorithm - it iteratively creates clusters out of similar-looking data points. The evaluation metric we're currently ...
4
votes
1answer
78 views

Extracting maximum information from a set of exam answers and their scores

Imagine we have a multiple-choice exam with N questions. Suppose we have a set of K answer sheets to the exam and their total scores (1 for a correct answer on a question, 0 for incorrect). How much ...
1
vote
2answers
430 views

Application of cosine similarity to detect plagiarism

Can anyone tell me how using cosine similarity to see the correlation between two documents actually shows you if someone is plagiarising the other? I understand how cosine similarity works but don't ...
0
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0answers
38 views

Is k-means parallelizable (other than the data parallelism of the distance function computation)

The k-means algorithm is known to be NP-hard. While the distance function computation in the algorithm loop is data parallel, the algorithm is iterative and may become exponential in the number of ...
0
votes
1answer
184 views

Automatically generate meaningful queries for a data table

My field of research is not Database or AI. But I have some problems to solve, and would like to know which branch this kind of problems belong to, and what are the results. The main question is: ...
0
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0answers
73 views

Activity prediction in a kitchen

Here is the scenario: There are three chefs(A- main chef, B and C- assistant) working together to prepare a diner set. The sequence of the event is as following. Start: The three chefs enter the ...
-1
votes
1answer
2k views

difference between multilayer perceptron and linear regression

What is the difference between multilayer perceptron and linear regression classifier. I am trying to learn a model with numerical attributes, and predict a numerical value. Thanks
2
votes
0answers
33 views

Baseline approaches for likes prediction

I have a small user-item matrix (25k x 1.8k) describing how users liked or disliked some of the items. Users don't have any attributes but items have several features. I would like to be able to ...
-1
votes
1answer
61 views

Training Error & Convergence to True Error

I Take some online class for Machine Learning. one of teacher say this sentence. if we have m data points, the training error converges to the true error as m → ∞. i thought, this sentence not ...
0
votes
1answer
174 views

VC Dimension Calculation for Intervals

As i See in ML Course a VC dimension calculation is very theoretical. What is the VC-dimension of intervals in R? The target function is specifieed by an interval, and labels any example positive ...
-1
votes
1answer
51 views

Policy function π in Reinforcement learning unclear

I have one question about policy function in Reinforcement learning. in fact this function indicates which action should be done in each state? Or this function indicate for get the ...
-1
votes
1answer
69 views

Selecting a M.S. in CS focus [closed]

I need to pick a focus in my Masters program. The running candidates are Networking Bioinformatics Data mining Computer Image Recognition In order to avoid this becoming a discussion, I'd be ...
6
votes
3answers
4k views

Word Frequency with Ordering in O(n) Complexity

During an interview for a Java developer position, I was asked the following: Write a function that takes two params: a String representing a text document and an integer providing the ...
0
votes
2answers
28 views

Determine Epsilon for identification [closed]

I have a project in which I need to compare different distances in a database with a distance in input in order to identify a person. For that I use this expression: DistanceDB - DistanceInput < ...
1
vote
2answers
153 views

Need an algorithm to find the input factors that are most affecting the output

I apologize if this question is already answered and appreciate any pointers to existing answers. I'm not familiar with statistical or data mining terms so my search was limited to basic words used in ...
2
votes
1answer
149 views

Best algorithm for correlation between time series?

I have some biological data (ECG), which are quite chaotic in nature, and and some other data; that are not chaotic but related in some way, like fatigue. I want to find out how the time series, ...
3
votes
0answers
56 views

What are some of the methods that NLP practitioners use to automatically learn linguistic features from text? [closed]

I am learning about NLP, with an eye to starting some practical NLP projects. I see that many of the algorithms for relation extraction and named entity recognition require you to identify linguistic ...
2
votes
1answer
36 views

Subspace clustering with random transformation

One approach for clustering a high dimensional dataset is to use linear transformation, and the most common approaches are PCA and random projection (where random projection arises from the ...
3
votes
1answer
179 views

Why linear transformation can improve classification accuracy when the dimensionality of data is high?

Let $X$ be an $m\times n$ ($m$: number of records, and $n$: number of attributes) dataset. When the number of attributes $n$ is large and the dataset $X$ is noisy, classification gets more ...
3
votes
0answers
46 views

Document clustering for summarization

I am curious as to what steps one would reasonably need to take to perform an extraction-based text summarizer. I've taken a look at some papers I've found on Google such as this one, which explains ...
2
votes
2answers
99 views

What kind of model is used by 20 Questions?

Which kind of machine learning concept / model is used in 20 Questions? Is this kind of thing best solved by a neural network? Where I can read something about it?
3
votes
2answers
68 views

Physical Meaning Behind Matrix Factorization

As we all know, Matrix Factorization is an effective method to do rating prediction jobs in recommender systems. Thanks to the work of Yahuda Koren. My question is why MF can do this job? What's the ...
0
votes
2answers
58 views

web content “mining” using supervised learning tequniques

We're accessing an API of a web system for obtaining product information. We require some additional information, which is not available through the API. This information is publically available for ...
3
votes
2answers
126 views

Decision Tree with Unbalanced Data

I have a data set with two classes: one class has at most 2000 members while the size of the second class is unlimited, though it is typically in the hundreds of thousands. I have read that it is ...
1
vote
1answer
25 views

Model for diurnal nature of data [closed]

I have a timeseries dataset of a quantity measured over the period of a week. I want to verify if the data is varying in a diurnal fashion with the help of some mathematical measure. Does any such ...