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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16 views

NLP methods specific to a language?

What NLP methods / algorithms depend on the features existing only in some languages? For example, does French has any NLP algorithms that English NLP and Spanish NLP do not have?
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Is there a theorem of prominent Russian mathematicians that played an important role in the development of machine learning? [closed]

I once attended a seminar in which a statement answering the question asked above was answered in the affirmative. I do not recall further specifics, however.
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Transforming RGB to inputs for neural network

I have the RGB values from image and i want to make the neural network to recognize and see the colors like humans, is there an algorithm to train neural network with color images? How can i make the ...
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Difference between rulefit & skope-rules Python Packages

RuleFit is an implementation of a rule-based prediction algorithm based on the rulefit algorithm from Friedman and Popescu (PDF). skope-rules Skope-rules is a Python machine learning module built on ...
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Can somebody explain me the meaning of this sentence? (Color Similarity - Selective Search Algorithm)

This is a sentence from this article : Color similarity: Computing a 25-bin histogram for each channel of an image, concatenating them together, and obtaining a final descriptor that is 25×3=75-d. ...
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How to select the best parameters for GridSearchCV?

I've created a couple of models during some assignments and hackathons using algorithms such as Random Forest and XGBoost and used GridSearchCV to find the best combination of parameters. But what I'm ...
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Algorithm to determine a single output value based on multiple input values [closed]

The main challenge is the lack of data. Input values come from tests results of patients. A patient takes a breath test at an interval during a timespan. The result values can range from 0 to ~200, ...
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Solve for the set of coordinates that reduces the average distances between request and server in half

I generate a DataFrame with coordinates and distances to 3 servers. ...
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What are the use-cases for heapsort option in numpy.sort()?

Could anybody share experience about use cases of the heapsort option in numpy.sort() (or pandas.DataFrame.sort_values()) in the data science field? I mean if the <...
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Using nearest neighbour as mapper of xy coordinates

This is my first post here so I apologize if this is not right place for this kind of question. I am looking for some tips on using (k)nearest neighbor algorithm as a mapper of hypothetical position ...
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Heuristics in A* algorithm

I am trying to implement the A* algorithm into a graph I have, but I'm not sure if I am doing it properly. So basically I have some nodes and some edges. In my case the edges are a cost, e.g. dollars ...
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Deep Learning model for classifying skin diseases

I have planned to create a deep learning model that classifies skin diseases(around 5 to 7 diseases). Please suggest me a good deep learning model to go with. I am planning to integrate this model as ...
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Order of eigenvalues when using different methods

I'm doing PCA in a covariance matrix where each column and row represents tenors of the yield curve. I have coded the Jacobi rotation method and I also have a QR algorithm based on numpy.linalg.qr in ...
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How to Identify Repeating Data Entries when the Repeated Entries are Spelled or Constructed Differently

I have a dataset of entries and a variable for the owner of the entry. Some of these people occur more than once. However, the names are sometimes written differently. I want to eventually be able to ...
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How to score the health of a company? [closed]

i'm currently doing dual apprenticeships. My main mission is to represent the health of a company based on accounting records for multiple companies over multiple years. The part of an accounting ...
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Estimate eps value in DBSCAN using KNN algorithm

I would like to estimate the best eps value for the DBSCAN algorithm on this dataset by following this set of rules: Set a minPts: 10 Compute the reachability distance of the 10-th nearest neighbour ...
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What is the difference between AI, ML, NN and DL? [closed]

What is the difference between the following four categories: Artificial Intelligence (AI) Machine Learning (ML) Neural Network (NN) Deep Learning (DL) Data Science My current understanding is that ...
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Does my prediction improve when I use more, but worse classifiers?

I have a logical problem when programming my tumor identification algorithm. In my data sample, I have tested multiple antibodies on tumors - to identify whether those tumors are good or bad. This is ...
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Click Through Rate calculation (CTR) calculation problem

So I'm doing a use case for a company interview and one of the questions is to calculate the CTR for a sorting algorithm. My question would be: Should I remove the operations where there were no ...
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How Should I deal with my imbalanced binary target [closed]

I am trying to model my data with Python and i am having concerns about my binary target variable, because it has 90% cases falling in 0 and 10% of the cases falling in 1. I have tried upsampling my ...
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Matching financial reconciliation data / matching multiple rows based on column values

I'm working with financial reconciliation data and the ask is to train the algorithm to match transactions (that are otherwise manually matched if the existing application didn't because not all the ...
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Deep Continious Clustering algorithm - just one output cluster

I use the DCC algorithm to cluster some data. The whole algorithm is available here, but shortly it is: construct mkNN graph of the data points (the connected components of it are the clusters). ...
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What algorithmic solution would you use for this scenario?

The Project In a Nutshell Use an algorithmic solution to predict with 70%+ accuracy in as close to real-time as possible the increase and decrease of at least three numeric incremental movements for a ...
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How can a ML algorithm learn to classify fake news? [duplicate]

I am new in Machine learning techniques and in fake news detection by using these algorithms (SVM, nn, logistic regression,..). I would like to understand how an algorithm can learn from a training ...
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Proximity multi-dimentional arrays. Which algorithms are commonly used?

I'm new to data science so still learning so much. I've been searching for proximity algorithms but I'm not sure which are suited for multi-dimensional arrays. Any guidance would be greatly ...
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Finding linear regimes in data

I am trying to find all linear regimes in a certain plot, given certain data points. If you are given two vectors of data $y$ and $x$ and $y$ is some possible non-differentiable function of $x$, how ...
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Triplet optimization producing a weird diagonal line?

I'm pretty sure this is the right forum for this, or let me know otherwise, I'll happily move this to a better place. I have a strange problem. I've written an algorithm designed to take three files ...
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What is the meaning of Information with respect to interpretability approaches in machine learning?

I was going through a pre-print on arXiv named "Quantifying interpretability and trust in machine learning systems". There, I found that a comparison of two interpretability approaches - ...
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Binary classification: how to transform features in real numbers?

I want to train a binary classification algorithm for spam detection using labeled data set. The dataset has the following features: ...
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Do learning rate scheduler have any significant improvement or redundant on Adam optimizer?

As in paper, Adam optimizer is adaptive learning rates algorithm. Is learning rate scheduler become redundant when use with Adam and AdamW ? Is it best practices to use learning rate scheduler with ...
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Good mathematically explained algorithm for Hyperparameter Optimization (Bayesian) for implementing in Java

I have implemented Random Forest, Bagging, Gradient Boosting, etc... in java myself. It took a long time to complete these machine learning algorithm codes. But at last all of them are well running. ...
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Which algorithm to use for transactional data

I'm given a Dataset of transactions and asked to find insights for businesses. I'm extremely new to ML / Data science and have only been experiencing with KMeans. The dataset has the following ...
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Decision Tree : how to determine target in a model with no labels?

I am studying classification algorithms using decision tree approach in Python. I would have some questions on this topic, specifically regarding the target (y) in my dataset. I have a dateset made by ...
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Stacking and Ensembling methods in Data Science

I understand that using stacking and ensembling has become popular, and these methods can give better results than using a single algorithm. My question is: What are the reasons, statistical or ...
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Algorithm query for bank customer segmentation

I've been using k-means clustering for bank customer segmentation up until now and I'm looking to explore other clustering algorithms in the banking domain. Is it a good idea to use affinity ...
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Expectation Maximization Algorithm (EM) for Gaussian Mixture Models (GMMs)

I'm trying to apply the Expectation Maximization algorithm (EM) to a Gaussian Mixture Model (GMM) using Python and NumPy. The PDF document I am basing my implementation on can be found here. Below are ...
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How do I select the “best” unsupervised machine learning algorithm to cluster my specific dataset?

I want to cluster a dataset without prior knowledge on the correct amount of clusters. For different algorithms (i.e. k-means, gmm...) I can iterate through different values and try to find the best ...
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What is the name of non-neural network algorithms

i am writing papers for my academic degree on machine learning. everytime I get confused when I try to put a name for standard algorithms (KNN, Linear Regression, Random Forest, etc) ( the non-neural ...
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Best algorithm for the chains of events

I have a big amount of customer journeys, where CJ is a sequence of user interactions with the site. It looks like: read an article in the blog -> checked the special offer -> watched video about the ...
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1answer
50 views

kMean clustering for recommendation

I have a file with 50000 rows from a library platform. Each individual row saves a user, and shows the order in which the user, has selected. The books could be from various categories (e.g. roman, ...
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Optimal graph search algorithm for probabilistic world

Greeting, i have the following world: ~500-600 states ~4-5 action per state. 4 of the states of a coin on them. Some action are probabilistic (for example "Jump from A to B,C" , has 20% of ending ...
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121 views

Creating a generic mathematical formula using a genetic algorithm

Assuming all of the following; I have 4 known numbers, all within a 0-400 range, like this: ...
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Meta Learning: how to train a model with Support Set and Query Set

I've just started to learn Meta Learning reading the book Hands-On Meta Learning with Python. I think I know the answer for my question, but I'm a little confuse about how to implement the algorithm ...
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52 views

How to choose the best algorithm

this might be simple but I need to know how to choose a best algorithm based on a scenario. I have a dataset. The target class is, let's say color, this ...
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Analysis of Alternating Decision Tree on Weka

I am applying the AD Tree algorithm & this is the tree visualization of the output: I can't understand the values in the decision nodes (-0.4,0.541,-0.882...), How are these calculated? & how ...
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Is there any way to calculate a relevance score between a title and the content of a text?

My question might sound a little bit stupid but I am trying to come up with a way to measure the relevance of the title of a text, let's say a piece of news headline, to the content. My idea would be ...
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Different Decision Tree pruning method

I am trying to learn different pruning methods for decision trees. I have put together a list of methods below. Reduced Error Pruning Cost Complexity pruning Minimum error pruning Pessimistic Error ...
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129 views

What is the scalability of linear regression and decision trees?

Recently I'm studying machine learning algorithms among them linear regression and decision tree so I have a question regarding the scalability of both algorithms. Can anyone provide what is the ...
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72 views

gradient descent diverges extremely

I have manually created a random data set around some mean value and I have tried to use gradient descent linear regression to predict this simple mean value. I have done exactly like in the manual ...
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135 views

When to use k-medoids over k-means and vice versa?

I had someone ask me about k-medoids at work and don't know about the performance of this algorithm over other clustering algorithms (namely k-means as it is most similar to it). In this case, it was ...

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