Questions tagged [algorithms]
An unambiguous list of computational steps involved in finding a solution to a class of problems.
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1answer
17 views
Prior/degree of belief/degree of lack-of-information/algorithms/complexity
For a long time I had a bit of difficulty understanding what "degree of belief" means.
Recently I had some thoughts about it and I wonder if they make any sense, or is there some literature about ...
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0answers
14 views
Can we mix the algorithm?
The question comes from when I was wondering about the cross-validation, finding out the best algorithm.
Then I got the question like if this model did a better job than the other, can the ...
2
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0answers
11 views
Algorithms for combining Bayesian networks? [on hold]
Are there any algorithms for combining multiple Bayesian networks? For example, let's say I have 5 variables A, B, C, D and E, and I build 5 Bayesian networks on different random subsets of these, let'...
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0answers
11 views
Stacking Algorithms - Should Certain Algorithms Not Be Used In Conjunction
Are there any reasons why one wouldn't want to use certain algorithms together in stacking?
For example, if I decided to use an SVM and a LogisticRegression classifier and were considering adding a ...
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0answers
4 views
How does Kamada & Kawai Force Directed layout algorithm interpret negative edge weights?
In Cytoscape, the Kamada & Kawai Force Directed layout algorithm is able to take negative weights between edges. Does anyone know how it's actually using the sign of these? Is it forcing ...
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0answers
5 views
Which algorithm(s) to use for quote price recommendations based on win/loss percentages by x date range?
I have a problem I'm trying to solve and was hoping someone smarter and more experienced may be able to help me out. Let me describe the problem. Thanks for any help in advance.
My company provides ...
1
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1answer
36 views
Multi-class Decision Forest vs Multi-class Decision Jungle
guys.
I have been learning about machine learning using Azure ML service from Microsoft and my team and I have seen that there are some multi-class decision algorithms, the Forest and Jungle are ...
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0answers
6 views
Ordered aggregated choices given users preferences
I have an issue creating an ordered list by preferences. Let's say I have 3 users (u1, u2, u3) and 10 topics (t1,...,t10). Each ...
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0answers
25 views
Cross - entropy for two variables with different prob. distributions
Let us say that we have given two random variables with different prob. distributions:
A = [0.1, 0, 0.5, ...]
B = [0.3, 0.1, 0.03, ...]
What should I do when I want to compute the reformulated cross-...
1
vote
1answer
19 views
For a specific dataset do all the features have the same importance across different algorithms?
I wonder if by implementing a feature selection technic using training with a specific algorithm you can select the feature you need to use with other algorithms also.
To be more specific after I ...
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2answers
59 views
Deep Neural Network visualization on multi dimension datasets [closed]
I have seen the PlayGround of Tensorflow. But it is using only 2D values which means only 2 inputs are taken.
I have 7 inputs and the output is only 1.
See the datasets sample:
...
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0answers
17 views
Epsilon from Bivariate Normal Distribution [duplicate]
I came across the following example from a book. I am given a dataset generated from a bivariate normal distribution:
Among the data, there are missing values for the last 20 of x2i (but not for x1i)....
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0answers
28 views
Computing Wassertein Distance
For two probability measures $\mu$ and $\nu$, the Wassertein Distance is defined as $$W_p (\mu , \nu) = \left[ \inf\limits_{\gamma \in \Gamma} |x-y|^p \, d\gamma (x,y) \right] ^{\frac{1}{p}} \, , $$
...
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0answers
20 views
Expanding known distribution over time with an algorithm
I'm currently struggling with the following problem:
An event reapeaditly occurs with an average interval of $m$ months for $n$ times (assume $m = 13.67$ months and $n = 3$ for the following example). ...
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0answers
20 views
Question about PyTorch tutorial
In this PyTorch tutorial
the backprop to compute gradients is shown with the following code:
...
0
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1answer
59 views
Questions about a k-means variant : recompute centroids after each point is reasigned
I have a variant of k-means, where the points are reassigned incrementally and I have a few questions about it.
Each time we reassign a point (we move the point from cluster $C_1 $to
$C_2$), we ...
2
votes
1answer
52 views
Machine learning algorithm test/evaluation sample size
I have recently implemented a machine learning algorithm as a part of a new credit risk scoring system. I would now like to evaluate the accuracy/performance of the algorithm when used in a "real ...
1
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1answer
53 views
Comparing two algorithms. Paired t-test, independent test or mixed effect linear regression
I have two algorithms running on 100 benchmark instances.
I want to test if there are significant differences in their mean average error.
A significant part of those two algorithms is not ...
0
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1answer
25 views
prerequisites to algorithms and then to python and Machine Learning
I spent the last 5 months studying full-stack web development using the MERN stack, that is (MongoDB, Express, React and NodeJs). Now that I have seen the full picture of what I would be doing ...
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1answer
26 views
How to quickly apply an algorithm with enough understanding
Let me take an explicit example.(the answer should be universal for any algorithm)
I want to group cities with similar average income together
I want to use dbscan to do this.(R/python/javascript/...
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0answers
40 views
Are algorithms that solve the k-center problem part of machine learning or computational geometry?
I am currently working especially with the k-center problem, which is e.g. used to determine optimal locations for k warehouses. This is done by defining k circles that cover a given set of points (...
0
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1answer
24 views
DECISION TREE : How to calculated for repeat decision noded such as this picture (C5.0 Algorithm -Decision tree)
I confused about decision tree such as this picture why repeat decision node.Could you please explain that decision tree. thank you
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1answer
32 views
Comparing Supervised ML algorithms in R on same data set
I've recently embarked on my data science journey, and I've therefore also started a data science course.
In this course, we've received an assignment asking us to model a data set using different ...
0
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1answer
18 views
Detecting a series of measurements
This is somewhat nonstandard:
My input is a series of values (integers or reals), and my goal is to decide if this series is likely to be a series of measurements of some unknown phenomenon (be it an ...
0
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0answers
26 views
ranking metric for a specific use case
I am trying to find the best "ranking metric" for my problem but could not find any existing suitable metric, can someone help.
I'm interested in information retrieval.
For item there is a "...
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0answers
10 views
Methodology for comparing FEC campaign finance sources with candidates' votes on legislation
I am trying to compare a database of campaign finance contributions to candidates with a database of congressional votes, and see if I can unearth any causal relationships between campaign finance ...
1
vote
1answer
8 views
Manber's graph-partitioning algorithm implementation
I'm having trouble understanding a part of Manber's graph-partitioning algorithm, presented in A Text Compression Scheme that Allows Fast Searching Directly in the Compressed File.
Generally speaking ...
3
votes
2answers
31 views
How do I check the validity of a set of inequality constraints? [closed]
I have a table of inequality constraints, each with an "x < y" relation. How can I check this table for contradictory logic such as a < b, b < c, c < a?
For example
...
2
votes
2answers
68 views
The Universal Approximation Theorem vs. The No Free Lunch Theorem: What's the caveat?
The universal approximation theorem:
A neural network with 3 layers and suitably chosen activation functions can any approximate continuous function on compact subsets of $R^n$.
The no free ...
2
votes
2answers
48 views
Is there a clustering algorithm that maximizes average silhouette? If not, why not?
The average silhouette index of a clustering of data seems to be used to determine the hyper parameter $k$ (i.e. number of clusters) in clustering algorithms like $k$-means. Is there an algorithm that ...
2
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0answers
13 views
What are the simple methods to do an unsupervised cluster to stock return time series?
I am a student in finance and I am working on my thesis project. I am interested in doing a clustering to stock time series. I first read the paper 'Time-series clustering – A decade review' from ...
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0answers
9 views
Prediction problem- Build model using 6 months data and predict on one month data?
I have a data set which contains site usage behavior of users over a period of six months. It contains data about:
Number of pages viewed
Number of unique cookies associated with each user
Different ...
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0answers
17 views
Optimizing a sequence of events on a variable conditional on the event
I'm trying to understand how I would approach a problem aiming to optimize a sequence of events to maximize another variable. For example, say I start selling a t-shirt at multiple stores, where each ...
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0answers
41 views
Optimal Sequence Problem
Lets says I have 100 people that like to buy item x. They ask me to send them a message every time I have x available to sell.
Of the 100 people that like to buy item x:
1) Some people will pay more ...
0
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0answers
6 views
Grouping by equivalent path length
I have a collection of an arbitrary number of discrete "path lengths".
I'm interested in discovering some automated (preferably Excel or C++/C#/Java code rather than Matlab or similar) method of ...
2
votes
0answers
45 views
Efficient linear regression given columns of A rather than rows of A
I'm analyzing a large problem with a large $N \times M$ data matrix $A$, where $N$ is the number of observations, $M$ is the number of explanatory variables, and $N \gg M$. I'd like to perform single-...
1
vote
1answer
29 views
How can I use patterns from data analysis to make a predictive machine learning model?
I'm trying to make a predictive model that can predict how well a product will sell in the future based on certain parameters. I've made some visualizations showing the relationship between the data. ...
1
vote
1answer
39 views
What are some good canned classifiers for high-dimensional data with probablistic labels, besides neural nets?
I've got a classification problem where my labels are $N\times4$ matrices of probabilities of class membership, and I've got about 1800 covariates. The covariates are mostly granular, in the sense ...
0
votes
1answer
35 views
Cross Validation in application of clustering on a collection of similarly behaving time series
I'm trying to understand how and at which point can one apply Cross Validation for time series data. If i'm not wrong CV increases generalisation so that our model has less bias in case the data is ...
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0answers
10 views
Multivariate fixed point iteration: the wrt variable on both sides of update equation and not are different?
I try to understand more about the update in multivariate fixed point iteration. I saw the examples where the updates have the same variable (the wrt. variable of partial differentiation) on both ...
0
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0answers
16 views
Optimize function on two stages
I have a non-linear cost function (which I do not know its analytical derivative and it is pretty hard to be computed). The function takes 8 parameters.
I need to minimize this function using some ...
0
votes
1answer
39 views
Given list symptoms and diseases - how to find similar symptoms based on data
I have a dataset of case studies like that:
Gender ; Age ; Symptom ; Condition
M ; 20 ; Fever ; Flu
F ; 29 ; Arm pain ; Trauma
F ; 40 ; Fever ; Cancer
M ; 90 ; ...
4
votes
2answers
58 views
Is there an algorithm for listing all/minimum admissable sets in a graph that satisfies the backdoor criterion in Causal Inference?
I would like to know if there exists an algorithm for finding all/minimum admissible sets in a graph that satisfy the backdoor criterion as defined by Judea Pearl in his book Causality (Please see ...
1
vote
1answer
31 views
Algorithm for selecting largest possible value, when observing online sequence of unknown distribution?
I have been trying to devise an algorithm for a problem that's been bugging me for a while. For some weird reason I haven't been able to find any mention of this problem in the literature, so far. I ...
3
votes
1answer
65 views
Is there a (matrix) operation that can count elements in vector pairs?
For two vectors $x \in \{0, 1, 2\}^{n}$ and $y \in \{0, 1, 2\}^{n},$
I need to generate a matrix $C\in \mathcal{R}^{3\times3}$ where $C_{i,j}$ equals the number of indexes $t$ where $x[t]=i$ and $y[t]...
0
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1answer
63 views
Difference between Hartigan & Wong Algo to Lloyd's algorithm in K-means clustering
In the iterations of Hartigan and Wong Algo of K-Means clustering, If the centroid is updated in the last step, for each data point included, the within- cluster sum of squares for each data point if ...
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0answers
20 views
best statistical approach to study the time evolution of clustering in a data set
I am using a stochastic method for the clustering of a data set. The number of clusters that this approach returns, can differ in each iteration. On the other hand, I would like to study the evolution ...
1
vote
1answer
81 views
Arithmetic operations on Random Variables [closed]
Firstly, I do not have statistics background other than a single lesson I took more than a decade ago, so I will use incorrect terms to explain my question. And probably it is one of the reasons that ...
-2
votes
2answers
65 views
Which clustering algorithm to use for dataset with high variance
I am working on an unsupervised learning problem and can use a little help for the same!
Objective:
To find out significant payment patterns or segments of customer who tend to have similar payment ...
0
votes
2answers
63 views
Optimization algorithm where calculating the function is very costly [duplicate]
I am doing physics simulation and have to minimize a function $f$ of approx. 10 parameters $f=f(x_1, x_2, ... , x_{10} )$. I have already looked into several optimization algorithms (downhill-simplex, ...
