# Questions tagged [algorithms]

An unambiguous list of computational steps involved in finding a solution to a class of problems.

735 questions
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### Using machine learning to predict entities

Im curious about an approach, since i start with machine learn a few months i wonder whats the best algorthm or approach to solve that: imagine that i have a entity like this: ...
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### Which bootstrap confidence intervals are provided by boot.ci in R?

I have reviewed a number of questions, but so far there is no clear answer on exactly which algorithms/procedures are implemented in boot.ci for R. For instance, 292619 mentions the types of intervals ...
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### KNN algorithm with variable k

I am a bit interested in KNN algorithm. I want to know whether there is a variant of this algorithm in which the k parameter is adapted automatically to the data dispersion.
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### Algorithm for Path Anomalies

I have a dataset: Person Path John Action 1, Action 5, Action 2, Action 50 Jane Action 4, Action 75, Action 23, Action 4 There are many actions, ...
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### Simple 'Trending' Forumla from total likes, first like + latest like

I'm trying to create a really simple list of trending songs. The data I have available: The first datetime a song was liked The latest datetime a song was liked Total likes datetime of now I'm ...
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### How Can I teach someone “sampling from a given distribution” is hard?

For many people I know, they do not think sampling from a given distribution is a hard problem in general. For example, many software provide functions do to sample from normal distribution or uniform ...
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### What are algorithm names for object counting in 3D space?

I am trying to use machine learning / neural networks to count how many units of an object type on front row of a shelf in a photo (let's call that object as "green beer"). As you can see in the ...
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### Is it possible to make a label automatically in supervised learning(Machine Learning)?

My background knowledge: Basically, supervised learning is based on labeled data. Using the labeled data, the machine can study and determine results for unlabeled data. To do that, for example, if we ...
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### Finding hidden sub-assemblies

I'm faced with an interesting problem and need some help finding existing best techniques to solve it. I suspect that the answer will end up being preparing data to run through R. Right now, I don't ...
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### Office Desk Rota Assignment problem

This is not a home work and the question is not related to studies (I am not a student). I have to do the weekly desk rota at the office and thought this forum might help with suggestions. My problem ...
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### Least absolute deviation line fitting [duplicate]

I want to implement robust line fitting over a set of $n$ points $(x_i,y_i)$ by means of the Least Absolute Deviation method, which minimizes the sum $$\sum_{i=1}^n |y_i-a-bx_i|.$$ As described for ...
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### Kohonen Self-Organizing Maps algorithm clarification. On each iteration, it goes trough all dataset or just a subsample?

If I understood the algorithm properly it should go like this: Randomly initialize SOM weights $\xi_1, ... , \xi_n$ in feature space. Randomly pick sample from training set v(k) (k as in step k) ...
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### How to design a complex machine learning system where individual classifiers can be retrained without modifying rest of the system?

I am designing a machine learning system which consists a bunch of classifiers (each output a confidence score between 0 to 1). Some classifiers consume output from other classifiers as features. Now ...
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### Mathematically Describing PCA chained with Logistic Regression

Python's scikit-learn package has a convenient pipe function that can combine machine learning techniques into one model with ...
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### Elman networks Training algorithm

What is the algorithm that is used to train an Elman Neural Network? and how it works? And what is the role of the context layer in the Elman model? Thank you.
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### Appropriate supervised learning algorithm for 200+ categorical variables predicting categorical outcome

CONTEXT I have a survey of 200+ multiple choice questions, most of which have different options (I was not the one who designed it). I have a categorical (yes/no) outcome variable. I'd like to find ...
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### Define measurement to test different data sets with the same algorithm

So I'm having an xgboost model "xgbm" which for a set of features, gives me a prediction between [0, 1] xgbm(f1, ... fn) = [0, 1] the model works fine and I ...
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### Difference between simulated annealing and multiple greedy

I'm trying to understand whats the difference between simulated annealing and running multiple greedy hill-climbing algorithms. As of my understandings, greedy algorithm will push the score to a ...
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### Nearest neighbor with lower value

I have a collection of p points in n-space, and a p-vector of scalar values corresponding to each point. In this example, p is much larger than n. Is it possible to build an R-tree (or some other ...
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### Likelihood of an algorithm-based function

Forgive me if this is a dumb question, but it is way outside of my area of expertise. Suppose I have an algorithm that produces some sort of a fit function, but that fit is not expressed in closed ...
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### Algorithms for solving combinatorial complexity problems in machine learning?

Many machine learning problems have combinatorial complexity. For example, in part-of-speech (POS) tagging in NLP, the goal is to predict one of possible $T$ tags for every word in a sentence of ...
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### Stability of maximum likelihood algorithm with indeterminate forms

Assume that I want to estimate a copula model, where the copula has a single parameter, $\theta$. When this parameter takes a specific value, say $\theta_I$, this copula converges to the Independence ...
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### Efficiency of the command pmvnorm in R

Let $X_1,\,X_2,\ldots,\,X_n$ be $n$ independent random variables, where $X_i\sim\text{N}(\mu_i,\,\sigma_i^2)$, for all $i\in\{1,\ldots,\,n\}$. Consider the $n$-dimensional random vector \boldsymbol{...
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### Find number of possible combinations of different sets that share elements

I need to find the total number of combinations of elements included in various sets (of different sizes). Each set may contain numbers from 0 to n. E.g. lets assume n=9. Thus, each set may contain ...
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### Two armed bandit with a known expectation

Assume a two armed case with bernoulli rewards. We know that UCB1 gives a pretty tight bound for multiarmed bandit cases. What if we know the mean of one arm, how can we obtain a better strategy/...
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### Measure non-randomness of numeric license plates

License plates for cars in Switzerland have the 2-letter abbreviation from the Canton and then between 1 and 6 numeric digits. There are no alphabet characters in the license plate, and therefore no ...
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### What is wrong with this self-made array shuffling algorithm? [duplicate]

I'm aware of the established array-shuffling algorithms, such as Knuth-Fisher-Yates. I'm interested in proving (or disproving) that my self-made shuffling algorithm is broken. It seems to be the ...
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### Are there any algorithms that give global optimum for K-Means?

The performance function of K-Means is minimum distance form the observations to the centroid of the closet cluster. For ideal solution we must find the real centroid of each cluster, but in ordinary ...
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### Ternary Decision Trees

In general, you want to check the performance of basic machine learning algorithm in default settings to get a feeling for the underlying structures, before picking a model. I know every ternary ...
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### How would I go about creating a recognizer for bills

Let say I have various electric bills, I want to get the account number and the payment total, how would you approach such a task? One of my ideas is to train a model to recognize different possible ...
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### Measuring simmilarity of observations (non numeric)

I have a dataset of format : day,measurement1,measurement2 1,a,b 1,a,c 1,f,s 2,a,b 2,a,c 2,f,g 3,a,d 3,a,q 3,f,s In this example day1 is more similar with day2 ...
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### Computing gradient w.r.t action, ReLU transfer

Foreword : I am new to machine learning and to this community, thank you in advance for your help. I am trying to implement this paper from Deepmind Continuous control for deep reinforcement ...
I have some non-uniformly distributed points in $R^2$ and want to calculate some statistics depending on their position using Python. I want to bin these points so that each bin has at least a minimum ...
$\newcommand{\R}{\mathbb{R}}$ In the context of the implementation of tree based models, suppose that a predictor space $X \in \R^n$ is under a partition process of the algorithm recursive binary ...