An unambiguous list of computational steps involved in finding a solution to a class of problems.
0
votes
0answers
8 views
Example for Predictive Modeling for Medical Devices using Python
Can anyone give me some example about:- How to do Predictive Modeling for Medical Devices using Python with dataset. And also which algorithm have to used.
1
vote
1answer
42 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
votes
0answers
18 views
Quantile repartition algorithm of D3.js library
I'm really new to stats so I may be totally wrong, but when I use a "quantile scale" with quartiles in D3.js with this dataset:
[3, 3, 3, 3, 3, 3, 3, 3, 6, 7, 8, 8, 8, 10, 11, 13, 15, 16, 20]
The ...
0
votes
1answer
19 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 ...
0
votes
0answers
12 views
Using Stats to provide a score for a daily rating with low sample size
Context
We have a register of people in our database, with a record of teams and leaders. Every day we send out a survey to each team asking them to rate their leader on whether they performed a ...
-1
votes
1answer
25 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/...
0
votes
0answers
36 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
votes
1answer
18 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
0
votes
1answer
31 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
votes
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
votes
0answers
21 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 "...
0
votes
0answers
19 views
i-th attempt in drawing a question from a set of Multiple-choice questions
I have a training set with $n$ records. For each record $(x_i, y_i)$, $m_i$ questions are drawn from a question bank with $p$ questions. Each question $j$ is a multiple choice question with $q_j$ ...
0
votes
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
7 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
30 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
43 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
42 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
votes
0answers
12 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 ...
0
votes
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 ...
0
votes
0answers
13 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 ...
1
vote
0answers
39 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
votes
0answers
5 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
44 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
28 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
34 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
26 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 ...
-1
votes
0answers
12 views
Necessity of independence assumption in Pareto sampling design
Suppose we have a finite population $\mathcal{I}_N$ of size $N$. Given $N$ positive numbers $\lambda_i$for $ i=1\dots N$ such that $0<\lambda_i<1$ for all $i$ and such $\sum_i^N\lambda_i=n$ ...
0
votes
0answers
8 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
votes
1answer
37 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
55 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
27 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
64 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
votes
1answer
48 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 ...
1
vote
0answers
16 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
55 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
55 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, ...
0
votes
0answers
29 views
Sample covariance matrix notation
I do not understand this notation for the sample covariance matrix (from Artificial Intelligence: A Modern Approach, Peter Norvig and Stuart J. Russell, Section 20.3, EM algorithm):
$\Sigma_{i} = \...
4
votes
1answer
127 views
What is a good algorithm to match the class distribution of two data sets?
I have data generated by a Monte Carlo simulation (let's call it MC) and a second data set (let's call it data), each having events in two classes 0 and 1. I am trying to write an algorithm such that ...
2
votes
0answers
99 views
Vapnik-Chervonenkis Dimension
My question has to do with the VC dimension of the class of convex polygons with $m$ vertices. A solution to this problem is given in the following: Advanced Algorithms.
Call the class of all ...
0
votes
1answer
31 views
General form of a machine learning algorithm
This is the general function that represent any machine learning algorithm:
$Y=f(X)+\epsilon$ , where $Y$ is the dependent variable, $X$ is the independent variable and $\epsilon$ is the random error ...
0
votes
0answers
35 views
What´s the best way to compare 2 ranked lists among the same dataset. (health informatics)
I´m working in an algorithm that weights coded health problems in electronic health records of single patients.
I´ll create a gold standard of the ranking (namely: heart faliure>diabetes>hypertension>....
1
vote
0answers
42 views
Logistic regression on HDFS, what's the algorithm?
How does Spark (or something similar) estimate a logistic regression model, or any statistical model that is estimated by an optimization algorithm, when the data are stored in a distributed ...
1
vote
1answer
66 views
Detect visual attention area in an image [closed]
I'm trying to detect the visual attention area in a given image and crop the image into that area. For instance, given an image of any size and a rectangle of say LxW dimension as an input, I would ...
5
votes
0answers
104 views
Good choices of PRNG for uniform circular (directional) data?
I'm planning to simulate iid one-dim variates with continuous uniform distribution on a normalized circle (which circumference is $1$ instead of $2\pi$). Namely, a sample consists of $n$ points ...
0
votes
0answers
59 views
Applications of FFT algorithm in statistics? [duplicate]
Are there any applications of the FFT algorithm in basic statistics i.e.: estimating a density distribution?
I would like to learn more about it - and it would be nice to work on an actual example ...
0
votes
0answers
21 views
Markov Chain Monte Carlo [duplicate]
what are the differences between M-H algorithm and M-H-within-Gibbs algorithm. If possible, upload for me the two algorithms please.
4
votes
2answers
108 views
Is it possible to train a machine learning model to predict the next prime number?
As there are no patterns to prime numbers. Is there any way in which ML could predict it?
0
votes
0answers
44 views
Examples of machine learning algorithms where it is not recommended to scale/normalise/mask the data?
We need to share company internal data with a vendor. In order to protect sensitive data, we have masked personal information such as customer id etc. We are discussing the pros and cons if we should ...
2
votes
1answer
45 views
What algorithm to use to predict customer count given past data?
I want to predict the number of customers on an hourly basis in a store given its previous data regarding how many customers came in the store per hour. The prediction would look like something below:
...
