An algorithm is a 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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Recommendation system and baseline predictors

I'm participating in programming contest, where I have a data, and where the first number is a user, second number is a movie, and the third is a number in then-points rating. ...
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21 views

Algorithm to identify a correct input for only one number [on hold]

Hello I'm hoping that you good folks here at CrossValidated can help me with this. I'm looking for an algorithm that takes an integer as an input and returns two types of values. One type of value ...
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7 views

What is the same or similar alogrithm in Weka for scikit-learn GradientBoostingRegressor?

I'm trying to move a GradientBoostingRegressor model to Weka. I have tried AdditiveRegression with different BaseLearners but the performance is very poor ( in terms of model quality and speed). I ...
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1answer
36 views

Computational complexity for linear discriminant analysis

The linear discriminant analysis algorithm is as follows: I want to conduct a computational complexity for it. For each step, the complexity is as follows: For each $c$, there are $N_cd$ ...
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1answer
26 views

Comparing classification algorithms using cross validation and caret's train

I am having issues understanding some concepts of algorithm comparison/parameter optimization/cross-validation in R Let's say I want to compare two classification algorithms, such as Random Forests ...
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8 views

Explanations about the parallel tempering

I am reading this paper on parallel tempering but there are a few things I do not really understand. If I'm not mistaken, parallel tempering is a MCMC method which is quite convenient to sample from ...
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24 views

Operations research problem to solve for out of stocks [closed]

I have a mathematical problem that I'm trying to solve and am wondering what kind of algorithm I should be looking at. I thought the revised simplex method would work but then I get stuck on knowing ...
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7 views

How to compute non-neighboring correlations using belief propagation?

Belief propagation is an algorithm to approximate the marginals of an arbitrary probability distribution. In principle, it allows you to compute the joint marginals at each factor node, which would ...
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2answers
201 views

Can humans cluster data sets manually? [closed]

Can human cluster data sets manually? For example, consider the Iris data set, depicted below: Instead of using clustering algorithms like connectivity-based clustering (hierarchical clustering), ...
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1answer
17 views

How to compute the $\chi^2$-table values?

How one can compute the values of $\chi^2$-tables? I saw two tables where was given for example that if degree of freedom is $1$ and $p=0.001$ then table value is in one table $10.827$ but in the ...
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10 views

Algorithm for multiple extended string matching [migrated]

I need to implement an algorithm for multiple extended string matching in text. Extended means the presence of wildcards (any number of characters instead of a star), for example: ...
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1answer
75 views

Optimizing parameter estimates by minimizing chi^2 in iterative procedure

I need to minimize my Chi^2 (bottom-left in figure 1) by adjusting parameter-values in a MLE-procedure (or something alike). The chi^2 (red) is a goodness-of-fit measure. It expresses how well the ...
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24 views

Are there differences between Delta TF-IDF and TF-IDF?

Are there differences between both algorithm or not ? i mean if i implement for ex Delta TF-IDF in a project instead of ...
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48 views

Sentiment Analysis - How should I handle negatively biased word list length?

I'm implementing a simple sentiment analysis algorithm where the authors of the paper have a word list for positive and negative words and simply count the number of occurrences of each in the ...
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1answer
22 views

Best Clustering Algorithm for Protein data

I have 400 virus genomes. In each virus, there are 100 genes (these are rough estimates). The genes in these viruses are transferred between each other very frequently. So Gene5 of Virus1 could be ...
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14 views

Method or Algorithm to produce near-accurate probability selection

Are there any known algorithms or methods to accurately identify, using random occurrences, the most probable next occurrence(s) as a pre-determined length of number set, by providing an already ...
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29 views

Different behaviors for different Ridge implementations in R

I am having trouble reconciling the different behavior of different Ridge implementations in R. As the following code demonstrates it seems that MASS:lm.ridge ...
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1answer
45 views

Transform sample to achieve target mean, skewness, etc

I have a sample of data with N values from which I calculate basic moments such as mean, standard deviation and skewness. I will then change these moments to different values according to my own ...
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19 views

Minimize difference between adjacent elements in an array [closed]

How can I calculate the minimum possible difference between adjacent integer elements of an array. For example: We have the array: 11 14 14 9 16 Adjacent ...
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1answer
185 views

Is there an optimal way to find the best division of an interval of some positive integers?

I am struggling with a conceptual problem. I have positive integers from an interval [1800, 1850]. For every integer from that interval, let's say (without loss of generality) 1820, I have about 3000 ...
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1answer
72 views

One-Max fitness function (Java)

Whilst searching on Google about Genetic Algorithms, I came across OneMax Problem, my search showed that this is one of the very first problem that the Genetic Algorithm was applied to. However, I am ...
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1answer
89 views

What is a good model for revenue managment / price optimization problem

I am trying to create a dynamic pricing model to optimize revenue for a hypothetical business. Lets say I have an application that connects dog walkers to people who want to pay for their dog to get ...
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1answer
25 views

clustering verifying two basic invariance properties

disclaimer: I already asked something similar on stack overflow, but it seems to be a better place for that question here. I recently became interested in axiomatic definitions of clustering, cf. ...
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50 views

Decision tree with adaboost

Helllo! I'm currently learning the AdaBoost algorithm to use it with Decision Tree. I want to implement everything myself (that's the way I learn - implement everything from scratch and later use ...
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10 views

Training a function that maps n-dim to n-dim

As an example, say the input is an array of numbers representing an audio snippet and the output is a transformed/filtered version of it. What would be the proper term for that? Which are examples of ...
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14 views

Expected number of replacements during weighted reservoir sampling?

Consider the problem of taking a weighted sample of size $K$ from a stream of unknown but finite size $N$ in a single pass. Reservoir sampling solves this by assigning each item from the stream with ...
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26 views

adaboost with multiple classification algorithms

Up to now I saw that all adaboost implementations use single classification algorithm and a training dataset as input and then creates multiple classification models by re-sampling dataset and uses ...
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100 views

On accept-reject method for unknown function

My problem is this I have a posterior as $Gamma(\alpha, \beta) \times exp(\lambda)$. $$Y_{1}^{n} \sim Gamma(\alpha, \beta)$$ $$\alpha \sim Exp(\lambda)$$ $$\beta \sim Exp(\lambda)$$ Now $n=50, ...
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20 views

How to implement Exponential Histograms

I am having trouble in understanding the concept of exponential histograms. They are known to be much efficient for maintaining statistics. I have read it in this article but cant understand how they ...
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23 views

Algorithms for invariant image recognition

I am interested in the current state of affairs when it comes to image recognition. I am particularly interested in algorithms that can handle a high degree of invariance. Except for Artificial ...
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1answer
91 views

Types of artificial intelligence with good results [closed]

I have been looking into artificial intelligence for some time now. I am wondering what branches are still in active research and have some good/interesting results. The two that I have looked in so ...
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1answer
77 views

Low Rank Matrix Factorization Collaborative Filtering - given a sparse set of feature data

I'm playing with a "minor" variation on an otherwise typical low rank matrix factorization collaborative filtering algorithm. I'm mostly following Andrew Ng's description in Coursera's online ML ...
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1answer
184 views

Clustering data into bins of variable sizes

I'd like to build a model (in R or excel) that takes in large amount of linear data and segments it into "bins". The linear data is an attribute that reflects what condition that section/record is at. ...
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3answers
91 views

what is the algorithm of getting maximum $D$ value in ks.test?

When I was writing R code to plot two empirical cumulative density curves, I came across ks.test in R. I looked into the code of ...
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29 views

Convergence Time of the EM Algorithm Depending on the Inital Parameter Values

I try to get an intuitive understanding of the convergence properties of the EM-Algorithm. I wrote a code that does the following experiment. We are given three coins: $H$, $A$ and $B$; with ...
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38 views

HMM walk through for backward algorithm with given example

This pdf file is a resource that walk through a simple HMM algorithm of two states http://www.indiana.edu/~iulg/moss/hmmcalculations.pdf, I have question in step 4.1 of the algorithm Specifically ...
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41 views

Is There A Machine Learning Algorithm For Textual Data With Thousands Of Classifiers?

I've been asked to migrate this from StackOverflow to CrossValidated. I have a problem that I think Machine Learning can solve but am having a very hard time determining which ML Algorithm to use and ...
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38 views

Basic questions about stochastic gradient descent / Robbins and Monro algorithm

I have a LOT of time series observations and I would like to estimate a simple AR(1) model $$ y_t =c+ \phi y_{t-1}+ \varepsilon_t \qquad \varepsilon_t \sim \text{N}(0, \sigma^{2}) $$ with parameters ...
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29 views

Fast way to compute central moments of a Poisson random variable?

I am looking for a way to quickly compute the central moments of a Poisson random variable. I've found a couple of resources on how to compute the central moments, but I'm still trying to figure out ...
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2answers
209 views

Why Adaboost with Decision Trees?

I've been reading a bit on boosting algorithms for classification tasks and Adaboost in particular. I understand that the purpose of Adaboost is to take several "weak learners" and, through a set of ...
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42 views

Algorithm to Rank “Risk Factors” on Individual Level from Logit Regression Scoring

I have a logit regression which predicts the probability of attrition. The equation is roughly: ...
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1answer
41 views

Noise removal from a dataset with a know distribution

If I have a dataset where it's points are drawn from a known distribution(For example a normal distribution) due to some noise the histogram doesn't reflect such a behavior (not necessarily skewed) ...
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36 views

Bound on the expectancy of the maximum level in skip list

Let $M$ be a random variable for the maximum level of skip list, $M$ is a positive integer, $k$ is an integer from 0 to $\infty$, and $$ \Pr(M>k) = 1 - (1-p^k)^n \leq np^k $$ In the article Skip ...
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28 views

Algorithm does not converge in R

I am doing a logistic regression in R, where I am modeling how potholes and weather correlate to accidents. When I run a logistic regression, I get the message "Algorithm does not converge" The ...
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38 views

Parametrizing a matrix (and algorithm) by its orthogonal complement

Given a large orthonormal matrix $U$, say $p\times p-k$ (with $k$ much smaller than $p$), is there an effficient way to parametrize $U$ by any matrix orthogonal complement (any orthonormal matrix ...
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1answer
31 views

Which Machine Learning algorithm: Sorted list of tags given metadata?

Our system allows an admin to manage a database of university courses. These courses have multiple fields, like the department, a title, and a description. I am adding the ability to add learning ...
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33 views

Support Vector Machine with zero bias term

I'm looking for an algorithm to solve SVM with zero bias term. So dual form of such SVM is $max_\alpha \sum_i^n \alpha_i -1/2\sum_i^n \sum_j^ny_iy_jK(x_ix_j)\alpha_i\alpha_j$ subject to: $0 \leq ...
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4answers
564 views

How to sample when you don't know the distribution

I'm fairly new to statistics (a handful of beginner-level Uni courses) and was wondering about sampling from unknown distributions. Specifically, if you have no idea about the underlying distribution, ...
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34 views

how to determine outliers in sample affected by ascertainment bias

I don't know if this is a really silly question as I'm in no way a statistician and I don't know if this is something that's actually quite rudimentary... Thanks for reading in advance too it got kind ...
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1answer
28 views

Algorithm for sampling points according to weights

In my current problem, I need to sample points in proportion to the weights assigned to them and an original probability density function. Unfortunately, the weights aren't known ahead of time and ...