Questions tagged [algorithms]

An algorithm is a set of one or more computations that will produce a calculated result. All statistics methods are algorithms. Algorithms can be simple, such as calculating a percentage, or can be very complex and require a computer for fast and accurate results.

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Assigning points to fitted planes

I’m working on a project involving fitting planes to 3D point clouds. The actual plane fitting part is working fine, but I’m trying to decide the best way to actually bound the fitted planes by the ...
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Predict a sequence given many sequences

I'm trying to find an algorithm that would fit this use case: My data: a bunch of fixed-size int arrays, e.g. [0,2,3,4,5] [1,2,3,1,5] [4,1,2,4,5] ... Input: an ...
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Which algorithm and/or libraries to use for prediction and probability matching of event (per second) data having numerical values?

Suggest algorithm to match input data with existing records and calculate matching probability. Based on matching probability predict the output similar to a matching record. Data contains per second ...
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What is the most effective unsupervised ML algorithm to use when outliers are present in data set?

I am analyzing a portfolio of about 225 stocks and have gotten data for each of them based on their "Price/Earnings ratio", "Return on Assets", and "Earnings per share growth". I would like to cluster ...
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Clustering a variable based on another variable or set of variables

df11[['COMPONENT_ID','FIRMWARE','SERIAL','CRP0_VDDN']].head() Consider I have these four columns to analyse. I want to form say 3-5 clusters of COMPONENT_IDs with ...
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How does the construction of a decision tree differ for different optimization metrics?

I understand how a decision tree is constructed (in the ID3 algorithm) using criterion like entropy, gini index, variance reduction. But the formulae for these criteria do not care about optimization ...
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I want to know which machine learning algorithms can be used for trajectory classifications?

I am working on project for clustering of air objects based on their trajectories. Like I want to train a model on dataset of different flying object's trajectories so later I can predict what type of ...
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What algorithm to use for finding artists/bands in text and differentiating between artists that share the same name

Here's the data I have: Text from articles from various music blogs & music news sites (title, summary, full content, and sometimes tags). I used a couple different NLP/NER tools (nltk, ...
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How do clustering works in Gravitational Emulation Local Search

I've been reading this paper titled Efficient clustering in collaborative filtering recommender system: Hybrid method based on genetic algorithm and gravitational emulation local search algorithm for ...
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Which algorithms should I use for identifying similar characteristics between data points (the intersections)?

I am working with a dataset that has been coded and categorized, so that each datapoint has a set of coded characteristics. An example data point would be something like the following: Example Data ...
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Understanding pseudocode for co-democratic learning

I am reading this blog from Sebastian Ruder blog-link, researcher scientist at Deepmind, and having problems understanding this pseudocode for Democratic Co-learning. Can somebody help me understand ...
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Help with algorithm approach for computer vision

I hope this is the right forum to ask. I had a client approach me with a demand for a vision system for their assembly line. The problem they are facing is that the operator sometimes forgets to put ...
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Clustering algorithms in pre-processing for classification problem

Through experience it was found that using k-means does not give accurate results to use them in pre-processing of classification, so if I use another clustering algorithm, can results be more ...
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How can you estimate the value of a component part where you only know the value of a whole?

I'm not sure how to frame this question, or where to start. I'm new to data analytics, but looking to develop skills and knowledge. An example of what I'm asking is if you have a retailers sales data ...
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Matching Algorithms in Python

We run a online marketplace for Commercial Real Estate industry and are looking to write matching algorithms to reduce the cost of search and transaction for the property owners/tenants. We have two ...
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In industry, what type of new data science algorithms does one develop?

I've seen several job descriptions for data science which include developing a novel algorithm to be a part of production environments. Can you give some input of what could be meant here exactly? ...
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What is a good method for detecting local minims and maxims?

I'm using kernel density estimation in order to compute probability density function for item (triangles in the figure) occurrence. Using this output, i want to find all the local minims and maxims. ...
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Machine learning solution approach to match loan repayments

I'm relatively new to the AI/ML space, but come from a programming background. The problem: I have a dataset of users transactions who have taken short-term loans from a single loan provider and I ...
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Need some info regarding string matching algorithms?

Let me explain a scenario to better explain my question, Assume I am working in a credit-card related company in which people uploads their receipts every month, I want to check if that person bought ...
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Need some advice on approach to select only the informative emojis from the data set?

I have a giant data set from a local elections, which contains hashtags, emojis, and comments. I wanted to make a network analysis using only emojis. So far I have a network analysis graph made in R ...
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How StarSpace works

I have gone through StarSpace algorithm but unable to understand how the output dimension is compared to Y (target variable) so that it can output the dimensions and loss function is optimized.
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Computational Complexity of Tucker decomposition

I am currently doing background reading for my Masters Thesis. I am working with tensor decompositions, whereby tensor I simply mean a multi-dimensional array. The aim of my master's project is to ...
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Best clustering algorithm to identify clusters and determine the closet cluster each individual response is near?

I have a survey where each question is related to a different 'shopper' type (there are 5 types so 5 questions). Each question is either binary (True/False) or scale based. IE: ...
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Training Machine Learning Model - Neural Network - Islands Problem

I was working on the following leetcode problem: Given a 2d grid map of '1's (land) and '0's (water), count the number of islands. An island is surrounded by water and is formed by connecting ...
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How to convert this forumal to a proper code?

I have the following formula [1] that I attempted to transform in to a function via R. However, my initial outputs are disconcerting. Before I go through many blocks (images), I am hoping to get ...
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Algorithms for classification / detection of hand gestures

I'm more or less new to machine learning, but I have a side project where I want to detect hand gestures in real time. Right now I'm using simple thresholds with if statements to detect static ...
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Clustering list of list of integers

I have ~100 sets of samples with integer IDs. For example, 3 of them could be: a = [0, 1, 3, 4, 6...] b = [1, 5, 9, 102...] c = [1, 7, 10, 42...] I am looking to ...
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What is the output polytree after aplying the Ramex algorithm to this graph?

I've been trying to understand the way this algorithm works, but I can't get a consistent result. It has two phases: the first one coverts a table of events into a graph, and the second where the ...
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What kind of loss function should be used for a problem like this?

My dataset consists of hierarchical timeseries. One could imagine it as "total sales" and segmentation per product. Something like this: ...
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Suggestions on how to explain 'models' & 'algorithms'

I guess other members of this Stack have ran in to this before, but I may be wrong: Have you ever been approached and asked to explain the difference between models and algorithms? This happened to be ...
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229 views

Is Annoy a machine learning algorithm to find nearest neighbor ? and is it similar to K nearest neighbor algorithm?

I was researching about Google universal sentence encoding and i saw that it uses simple neighbor/Annoy to find the nearest vector for semantic-similarity search engine. This is the first time i'm ...
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Time Series and forecasting individual reservations

What kind of algorithm would best for following problem. I try to forecast reservation of different kind of tables. Let's say I have 100 different tables, which are reserved for from 17.00-22.00 ...
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Image deblurring network (not a GAN)?

GANs take a long time to train. I have to train and use a machine learning algorithm (not necessarily a deep learning algorithm) that is able to deblur any image (after training it in about 10 hours: ...
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Latent Dirichlet Allocation in R, topicmodels using VEM algorithm or Gibbs Sampling mixing tm and topicmodels library or WarpLDA from text2vec?

If I am trying to classify 230k text abstracts, which option would be better and more precise when aplying LDA?
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How to approach the topical text categorization of a small collection of short texts?

I have a set of 200 very short documents, between 1 and 20 words each. One of my colleague would like to classify each of these documents in three predefined topics (let's call them "A", "B", and "C"...
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How to find bias for perceptron algorithm?

My question is very basic. I am starting with ML and am working on the perceptron algorithm. I successfully computed the weights for this input data: ...
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How can we conclude that an optimization algorithm is better than another one

When we test a new optimization algorithm, what the process that we need to do?For example, do we need to run the algorithm several times, and pick a best performance,i.e., in terms of accuracy, f1 ...
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Unsupervised Algorithm for hybrid data [duplicate]

I have a hybrid data that contains 15 categorical data and 4 continuous data. I need to implement a prediction on the data. So as I don't have any labeled data, I need to implement the unsupervised ...
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Finding the closest neighbour of multidimensial data point

I have a test point with 15 attributes. I want to find the closest data point to this test point from 10,000 data points. I'm thinking using something like this: ...
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Using Hausdorff Distance with Time

My company tracks objects. I have developed an algorithm that tries to identify objects that are attached to each other. It does this in real time and starts trying to identify objects after roughly ...
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Help with MLP convergence

I posted this question on AI SE and got advised to ask here for guidance. I've been stuck for a couple of days trying to figure it out how the standard MLP works and why my code doesn't converge at ...
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Clustering data by multiple values

I am trying to find a way to cluster/group students by their knowledge of different subjects. Given following as an example: ...
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How do I use this depth first search code to obtain a topological sort?

Problem: I need to implement a topological search using the following depth first search code. Note: The original code comes from here, and this is a problem given in at the end of the chapter. I'll ...
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How can I train a machine learning model with below characterstics? [closed]

Hi I have a classifier model to solve, which has close to 56k samples and 30 features which ...
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Selecting right cartons for meeting demand (retail supply chain)

I am working on an inventory allocation problem and I could use some help figuring out an optimal solution. Let's say a retail chain's warehouse stores inventory in cartons (physical boxes). Each ...
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431 views

Suggestions for Matchmaking Algorithm

I run a heterosexual matching making service. I have my male clients and my female clients. I need to pair each of my clients with their "soul mate" based on several attributes (age, interests, ...
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Model or algorithm for iterative optimization

Here is my problem : At every loop, I have new data that depends on the previous outputs. I need to approximate the function that optimizes (minimizes / maximizes) this new data on every iteration. ...
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Predicting probability for each tag given already chosen tags

I have a set of tags (~10'000, will be extended over time) presented to a user. After he has selected 3 or more tags, I want to predict for each remaining tag what the chances are that the user will ...
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Finding the usage percent to perform predictive analysis for new users

Problem Statement- I have to find the average feature usage all the users and the usage of user X to suggest if he should use the feature. Example - On google home page out of all the user's avg 85% ...

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