Questions tagged [algorithms]

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

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Help in providing insight for analysing this problem

I am trying to analyse a system, I have an application which consists of a series of components, the components are deployed on two different machines, the deployment of components to be placed on two ...
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Intuitive explanation of identity cards of the fields (optimization)? [closed]

In section 1.1.4, Nesterov (in his book convex optimization: https://g.co/kgs/8uYfRV) defines the style of research (or rules of the game) in the different fields of nonlinear optimization based on ...
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Least Squares Regression to Solve a Non-Linear System

I'm trying to solve the following non-linear system; $\sqrt{(x-x_1)^2 + (y-y_1)^2} + s(t_2-t_1) = \sqrt{(x-x_2)^2 + ( y-y_2)^2}$ $\sqrt{(x-x_2)^2 + (y-y_2)^2} + s(t_3-t_2) = \sqrt{(x-x_3)^2 + ( y-y_3)^...
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Science practice: Where to introduce approximations?

In my work, I am using an algorithm which relies on estimates of the gradient of the log-posterior at a collection of Monte Carlo samples. Since this gradient is not available in closed form, I must ...
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Uniform the distribution of characters in words dataset

I have dataset of text images, each image contain 1 to 3 words. I need to predicate the sequence of characters in these images, however the distribution is very skewed. I found an algorithm in a paper,...
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Checking Users in a Queue: Algorithm for managing Priority? [migrated]

Let's say I have a large set of users in a queue that I query each user against a rate-limited API periodically. Once all users have been queried, the process is restarted. The rate limit is applied ...
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Comparing Directed Unweighted Graphs with a Dissimilar Number of Nodes

I'm looking to compare 2 unweighted directed graphs and get an (ideally differentiable) similarity score. Both graphs describe a trajectory in a 2d space. The reference graph is a step by step guide ...
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How to do data mining that consider all possible variables specification?

First of all, I know the drawback associated with datamining in modelling, but this case is very specific, and my model don't need any replication. I just need to overfit the results of my database. ...
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62 views

Smoothing algorithm for anomalies

To construct a plot, I'm looking for an algorithm which can handle inf and (very) negative values. If I have infinity values everything is a line but not infinities. Example ...
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1answer
28 views

Find numerical approximation for MLE of marginal distribution approximation

Say that I have the joint pdf $p(x,y)$ for random variables $X$ and $Y$ and that I'm looking for the maximiser $x_0$ of the marginal distribution $p(x)$. Suppose further that $p(x)$ cannot be computed ...
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Is there an algorithm with linear time complexity to calculate the rank sum statistic?

Definition 1: For a real array $x = (x_1, \dots, x_n)$, denote the rank of $x_i$ in $(x_1,\dots, x_n)$ by the following: $$ r_{i}=\sum_{j=1}^{n} I_{\left(x_{j} \leq x_{i}\right)}, \quad 1 \leq i \leq ...
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How can I use Karman Filter or any other filter to better estimate Blood Glucose values and give the right amount of Insulin?

Right now, I just have Blood Glucose/ Time values and also the graph which contains those values. But, the obtained Blood Glucose values hardly remain in the desired range. So, I was wondering if ...
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How to find the best or optimal parameter value set for agent based or other kind of modeling?

I am doing agent based modeling (ABM) for infectious disease modeling, and the model has 50+ parameters which can any probability value between 0 and 1, or can be any float value from 0 to >0 (...
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How to randomly shuffle tiny spheres inside a big sphere? [duplicate]

I have a list of spheres with some known characteristics (ids, radii, masses, and positions) with ids, radii, and masses being 1D arrays with shape (511, ) and positions being 3D array with shape (511,...
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What could go wrong ignoring the even size case in computing the median value?

Given a list of $N$ numbers I need to compute the median. The book Numerical Recipes says that: When $N$ is odd, the median is the $k$th element, with $k=\frac{N+1}{2}$. When $N$ is even, statistics ...
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Logistic generalized Additive Model (GAM)

How are the smoothers fitted in case of Logistic GAMS? For Gaussian response variable, many smoothers are defined such as splines and local regression etc. But how are they used in case of Logistic ...
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In SARSA and Q-learning algorithms in RL, is policy updated during the iteration for Q-value learning?

In the video by Prof Brunskill "Stanford CS234 winter 2019 lecture 4" for model-free control (https://www.youtube.com/watch?v=j080VBVGkfQ), at 57:49/1:17:45, the pseudo code for SARSA ...
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Backpropagation through time for stacked RNNs

I was able to find the partial derivative of the cost function with respects to a single variable without much difficulty. However, this requires propagating backwards through the network for each ...
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How to define a skewed distribution using mode and two inflection points? [duplicate]

I want to define a skewed distribution function and plot it in python using the mode and inflection points parameter values instead of using the mean and standard deviation. For example, I have ...
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1answer
217 views

How to define a skewed normal distribution using mode and two points? [closed]

I want to define a Gaussian distribution function and plot it in python using the mode and inflection points parameter values instead of using the mean and standard deviation. For example, I have <...
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How to define a skewed Gaussian distribution using mode and two points? [duplicate]

I want to define a Gaussian distribution function and plot it in python using the mode and two points parameter values instead of using the mean and standard deviation. For example, I have ...
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Understand the implement detail of BayesianLinearRegression in python

I am learning the implement of BayesianLinearRegression through numpy-ml project I copy the code here ...
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Question about UCB and rewards in Monte Carlo Tree Search

need some help. What I'm having trouble with is the formula used to select the best node when exploring the tree. Modified UCB formula: Here wi is the number of victories of the i-th node. ni is the ...
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Preprocessing data for the learning step

I am currently reading "Human level control through deep reinforcement learning" and I came across the algorithm in the paper. I am confused because the algorithm uses a different notation ...
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How do you train a clustering model?

This should've been a pretty simple question, but I still have a few questions so I decided to bring the discussion here. The thing is, I have a group of products, and the historical dataset looks ...
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Estimation of Sparse Panel Data

There are 1000 students and 100 teachers. Each teacher is given the answer scripts of randomly selected 100 students. So in total 10,000 answer scripts are judged. Now this is sort of panel data, but ...
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Does the rate of convergence of optimizers matter in deep learning?

In classical optimization, an enormous amount of effort is taken to characterize the rate of convergence of optimization algorithms and designing fast gradient algorithms. You can find tables upon ...
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Are there any machine learning algorithms that are specifically designed for processing data with low signal to noise ratio?

I have a dataset which is made up of 62 features and 1 set of labels, all of which are percentiles. The signal to noise ratio is low. If I were to do a simple balanced classification, if I could ...
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Maximum-likelihood histogram from noisy data

Given a sequence of noisy observations $\{x_k\in\mathbb{R}\}$ and a set of thresholds $\{t_i\in\mathbb{R}\}$ we can bin the observations using the thresholds to create a histogram. However, since we ...
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23 views

Approximating a distribution with an integer histogram

Given a distribution $f:[0,a)\rightarrow\mathbb{R}$, is there a simple algorithm by which to find a sequence $\{h_i\in\mathbb{N_0}\}$ such that $f(x)$ is approximated by $h_{floor(x)}$ as a histogram ...
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1answer
24 views

Alignment algorithm

I am looking for an algorithm that can align a vector of numbers . I don't know exactly where to look because I am not sure how you would name it, so I am sorry if this is already asked (I couldn't ...
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Some detail questions about K mean algorithm

Question is how to set Kmeans algorithm K, what kind of data set is applicable, how to evaluate Kmeans clustering results, and how to judge whether the LR and Kmeans algorithms implemented by myself ...
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Are there ML algorithms for data whose probability distribution changes over time?

It seems ML algorithms are specialized for cases in which the population distribution is fixed. Cross-validation also wouldn't work well if the distribution would change over time. However, it is not ...
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1answer
29 views

Algorithm to estimate aggregated outcome variable

I am looking for an algorithm that can estimate weights for an aggregated weighted average. The difficulty is that my outcome variable is an aggregated group variable. I have the following data that ...
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Adam: A method for stochastic optimization - is there a way to adapt the method for negative gradient?

Below is the pseudocode for the Adam optimization algorithm. The original paper can be found here on arXiv. $g_t$ in the algorithm represents a vector of the gradient. Suppose that instead of the ...
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What is the difference between a decision tree and something called “subgroup discovery algorithms”?

I'm reading a paper which states that subgroup discovery is: ...
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Lexical diversity of a text segment in comparison to the whole corpus/dataset

I've been reading articles on formulas to measure lexical diversity, but I haven't found yet a possible solution to my problem. I've been able to implement in C# a few formulas to measure lexical ...
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1answer
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How do you find the minima of a function in python? [closed]

Say we have a quadratic function in x, where the domain of input x is Real Numbers. How can we find the minimum value of the function (output y) in a programming language like python? Immediately ...
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1answer
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Advice on anomaly detection algorithm for customer support data

Background In the customer support department, when customers contact us we categorize the interaction into the issues customers are having. For example, customer X contacted us about an issue “Order ...
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Is it normal to have inconsistent values of accuracy when running a classification algorithm?

I ran several algorithms on several datasets (i.e. SVM, KNN, Decision Tree, Naive Bayes, Logistic Regression and MLP). Due to it some randomization process in creating the training sets, the accuracy ...
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1answer
28 views

confidence interval for arbitrary distribution

Let's say I have some random variable $X$ whose CDF can be evaluated exactly but cannot be Inverted .Can someone given me an algorithm or some pointer to relevant source which talks about this.Every ...
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36 views

How to find the optimum split points for GBDT?

GBDT (Gradient Boosting Decision Tree) is an ensemble model of decision trees that are trained in sequence(i.e. an ensemble model of boosting). In each iteration, GBDT learns the decision tree by ...
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DBSCAN - can a point be a border point for two clusters?

I am trying to implement the DBSCAN algorithm but as I was coding, I realized that a point can be a border point for two clusters. Am I missing something? If this can happen, how do I deal with the ...
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Calculate standard deviation of a set of numbers in one cycle over the numbers without knowing average in advance [duplicate]

I have an set of numbers that I need to calculate standard deviation of. I want to do it in a single cycle over that set and I don't know the average of the array beforehand. I need it for my program: ...
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1answer
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What models/algorithms should I research to make a community-driven movie recommendation system?

Pretty new to ML so sorry if this question has been answered before. Dataset of: users (100,000 unique) movies (7000 unique) w/ genre data (action, comedy) and plot summary for each user, a list of ...
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Are all agglomerative clustering methods deterministic?

I'm going over the Agglomerative Clustering algorithm in sklearn.cluster.AgglomerativeClustering. It supports four linkage methods: Ward minimizes the sum of ...
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How can I incrementally calculate the 4 central moments in statistics (mean, standard deviation, skewness and curtosis) when a value is removed?

I'm incrementally calculating the 4 central moments. When a value x is added and n, M1, M2, M3 and M4 are some predefined values, I'm using the following algorithm: ...
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Identifying Proportion of Available Observations Used for Prediction in KNN

Assume you have $10$ covariates, $\mathbf{X}_1$ to $\mathbf{X}_{10}$, each of them uniformly distributed in the interval $[0,1]$. To predict a new test observation $(\mathbf{X}_1^{(0)},...,\mathbf{X}_{...
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Curse of Dimensionality: Identifying Correct Statement

Im trying to identify which one of these statements about the curse of dimensionality is correct: a) It means that the performance of the KNN classifier gets worse when the number of predictor ...
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Possible optimization algorithms for fitting a nonlinear model with no analytic solution (contains integrals that can only be solved numerically)?

I would be grateful for suggestions to solve the following problem. The task is to fit a mechanistically-motivated nonlinear mathematical model (4-6 parameters, depending on version of assumptions ...

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