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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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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13 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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24 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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9 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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8 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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86 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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16 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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16 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
69 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
60 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
134 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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71 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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20 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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31 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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38 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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24 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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25 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
92 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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30 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
35 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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31 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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24 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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25 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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26 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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28 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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550 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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28 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
24 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 ...
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2answers
446 views

Why doesn't runif generate the same result every time?

Why is it that random number generators like runif() in R don't generate the same result every time? For example: ...
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47 views

Finding a global minimum of non-convex quasi-smooth function that is costly to evaluate

I have a bounded non-convex function in 10-dimensional space. The function is quasi-smooth, you can imagine a histogram, here is an illustration, it just shows the idea and not related to my ...
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0answers
29 views

Efficient algorithm to enumerate all member DAGs of a Markov equivalence class

I'm working on a research project involving Bayesian networks. BNs are directed acyclic graphs (DAGs) used to compactly represent joint distributions of variables. In many cases, multiple DAGs can ...
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45 views

Quad precision normal cdf and quantile functions

I'm looking to run the normal distribution cumulative distribution function and quantile function (its inverse) using the quadruple precision floating point format. Does anyone know of a library that ...
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20 views

Algorithm recommendation for string classification

I have numerous (hundreds to low-thousands) of pre-classified short strings of text, each string is just a few words long, some just a single word. The strings have been divided into a few dozen ...
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10 views

Basis for a certain class of iterative algorithms [closed]

I have seen the following algorithm trick in a few places. Suppose that you have some closed form equation that you would like to solve, of the form $A=F(A)$, where $F$ may be rather complicated and ...
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171 views

Newton Raphson Over-estimates Parameters

I have implemented an almost plain vanilla algorithm to find the MLE estimates of 3 parameters in a log-likelihood function (in R.) When I test my algorithm with some simulated data it does pretty ...
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24 views

Comparison of supervised learning algorithms with different data types

I've been looking for review type papers of supervised learning techniques that focus on the type of data being used to train e.g. factors with many levels, binary factors, continuous variables etc. I ...
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2answers
27 views

What's the best algorithm type for low-dimensional grouping

I'm looking for some advice on directions to head in a project I'm working on. Basically what I want to do is identify general (of varying size) groups in a 2-D grid of points belonging to one of ...
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2answers
76 views

Understanding differences between large and small dimensional data when implementing algorithms

I'm working on a local outlier factor implementation based on the wikipedia entry : http://en.wikipedia.org/wiki/Local_outlier_factor This article seems to explain it in just two dimensional data. ...
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19 views

Discrete optimization with a very large solution neighborhood to explore

I have a problem whose feasible (discrete) solutions can measured by a cost function. I am thinking of using some optimization technique to get better solutions from a rough initial approximation. I ...
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1answer
30 views

How can one evaluate Incremental Clustering Algorithms, in particular the goodness of the clusters formed?

I have been studying an incremental clustering algorithm for a large set of data that exhibit an inherent dynamic behavior (that is new data can get added over time and some older data may get deleted ...
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51 views

Random forest - proof of convergence

I'm having some trouble understanding Leo Breiman's proof that the generalization error of a random forest converges as the number of trees increases (here's a link to the paper). At Appendix I he ...
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155 views

Calculate rating/score based on multiple criteria to rank data

I extract data related to a movie by sentiment analyzing the reviews. Hence,extracted movie data contains average sentiment values (avg_pos and avg_neg) calculated over multiple reviews, total no of ...
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46 views

The best way to solve particular classification problem?

I got training set (time series) of size approximately 2 million precedents {x,y}. Each x is a vector of size 20 and each y is a binary vector of size 10 like {1,0,0,1,1,0,1,1,1,0}. For a new input x ...
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1answer
32 views

Resources for Computational Algorithms

The journal Applied Statistics used to have a section on algorithms, which are available online. Griffiths and Hill also published a selection of these algorithms in a book in 1985. But I can't find ...
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532 views

What are the most popular artificial neural network algorithms for recognising the content of images?

What are the most used/popular artificial neural network algorithms for recognising the content of images in general? E.g. If the picture is of a person, dog, cat or a car. If the picture is a ...
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3answers
230 views

Library routine for rolling window lag 1 autocorrelation?

I am looking for a library routine that will calculate the lag 1 autocorrelation of a time series with a rolling window; meaning "slide a window of size N points along the time series, calculate the ...
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0answers
28 views

Finding related words

I have several files, each of which contains unique terms which are related to each other(without sentence structure). So for finding the word relationships I created a dictionary of bi-grams for ...
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117 views

Baseline predictors parametres

I've implemented baseline predictors model. It trains on data: "user_number item_number rating_ui" And then I need to predict raiting for "...
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1answer
39 views

Finding optimal combination of parameters for clustering

I have a spreadsheet with one object per line. Each column contains values that are parameters of my objects (let's say length, width, height, weight, color). I can classify objects based on color and ...