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Questions tagged [algorithms]

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

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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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1answer
600 views

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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17 views

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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9 views

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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1answer
107 views

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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53 views

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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1answer
35 views

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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2answers
16 views

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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1answer
50 views

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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59 views

What can be the reasons that L1-regularized NMF gets worse result than standard NMF in sparse matrix computation?

I apply L1-norm as a group sparsity constraint [1,2] into non-negative matrix factorization $V \approx WH$ for source separation. Objective functions: Standard NMF (Kullback-Leibler divergence): $...
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9 views

Possible methodology for putative combination of different statistics and metrics for ranking of functional enrichment analysis results

i would like to ask a general statistical question concering the ranking of some functional enrichment analysis results, regardless of technology (rna-seq, microarrays, etc), or methodology (GSEA, ...
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2answers
1k views

What are some important uses of random number generation in computational statistics?

How and why are random number generators (RNGs) important in computational statistics? I understand that randomness is important when choosing samples for many statistical tests to avoid bias towards ...
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0answers
148 views

What is the standard definition of a non-parametric machine learning algorithm?

According to my experience, the non-parametric term usually refers to algorithms complying the following definition from a clasic textbook [1]: A learning model that summarizes data with a set of ...
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1answer
73 views

Mathematical algorithm for bots detecting

I'm faced with the task and I need the help of senior statisticians.There are a lot of virtual gambling, for example poker, it is need to detect bots. There are a lot of fixed indicators (mouse ...
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0answers
43 views

Probability of adjacent elements not separated by more than 1 element

I am merging k sorted sets in C. What is the probability that two elements that are adjacent in the parents set are separated by at most one element in the final sorted set ? The parents sets are ...
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128 views

simulation of non-homogeneous poisson processes

When simulating non-homogeneous (time-dependent hazard $\lambda(t)$) Poisson processes, we can use thinning [1] to generate jump times $t \in [0,t^0]$: initialize $t = 0$ generate $u_1 \stackrel{d}{\...
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1answer
216 views

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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3answers
374 views

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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0answers
26 views

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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0answers
163 views

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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1answer
148 views

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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51 views

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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0answers
28 views

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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1answer
367 views

Clustering symmetric distance matrix

Below is a symmetric matrix $A$ with distances between observation $i$ and $j$. $$ \begin{matrix} 0 & 9 & 8 & 6 & 3\\ 9 & 0 & 1 & 7 & 8\\ 8 & 1 & 0 & 6 &...
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62 views

Is there a solution for Canonical Correlation Analysis on large sparse matrices?

I'm trying to run CCA over two views which are sparse matrices. The two views are very high dimensional (e.g. 300k, 400k) with 1m samples. CCA needs the input views to be zero mean but I won't be ...
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1answer
130 views

How to partition set of items into subsets with similar mean, variance and number of elements - looking for some help

Short version: Given I have a list of 120 traits (happy, sad, etc.) evaluated on a number of scales ranging from -5 (for example highly negative) to +5 (for example highly positive), how can I group ...
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1answer
131 views

Classification algorithm based on average distances from a test point to the points in each class

Is there any classification algorithm that assign a new test vector to the cluster of points whose average distance is minimum? Let me write it better: Let's imagine that we have $K$ clusters of $T_k$...
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1answer
361 views

Recursive Feature Elimination in sklearn

I have been thinking about one thing after reading documentation from sklearn about Feature Selection for building prediction models (http://scikit-learn.org/stable/modules/feature_selection.html#rfe) ...
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1answer
56 views

Initialization of lasso path algorithm

I'm trying to understand the LASSO-path algorithm that is described here on page 9&10 (Sparsity and the Lasso by Tibshirani & Wasserman, 2015). First they say we initialize $\lambda_0 := \...
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0answers
28 views

PLS Regression - fixed latent variables for Y (predicted variables)

I am using kernel PLS algorithm for my problem. I'm directly setting Y to a pattern I wish to search for in my data (there is a reason I'm not using Limma). There is a naive target Y which essentially ...
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1answer
49 views

Distribution of infinite sum $\sum_{t=0}^{\infty} \epsilon_t r^t $

In my current statistics course we're being taught about time series, and in this context we came across sums like this: $$\sum_{t=1}^{\infty} \epsilon_t r^t \quad \epsilon_t\sim \text{WN}(0,\sigma^2) ...
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1answer
1k views

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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1answer
160 views

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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1answer
47 views

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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2answers
126 views

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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0answers
56 views

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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1answer
114 views

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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0answers
37 views

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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0answers
59 views

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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1answer
44 views

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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32 views

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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1answer
168 views

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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1answer
312 views

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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0answers
12 views

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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1answer
30 views

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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3answers
1k views

Stopping criterion for Nelder Mead

I am trying to implement the Nelder-Mead algorithm for optimising a function. The wikipedia page about Nelder-Mead is surprisingly clear about the entire algorithm, except for its stopping criterion. ...
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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 ...
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Local binning of random points in R²

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 ...
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92 views

Identify categorical versus continuous variables in Tree based models

$\newcommand{\R}{\mathbb{R}}$ 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 ...