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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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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12 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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18 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
43 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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15 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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10 views

Viterbi for text segmentation

i have a question concern text segmentation to MWE (tokens) if a i have for example these two sentence: 1- " i read new york times" 2- " the population of india is equal to the population of new york ...
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1answer
29 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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21 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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22 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
19 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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22 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
536 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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21 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
21 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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43 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 ...
2
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0answers
24 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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35 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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14 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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84 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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21 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
23 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
67 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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18 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
24 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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46 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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101 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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45 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
31 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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3answers
247 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
160 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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26 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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86 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
36 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 ...
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2answers
185 views

How to compare the outputs of two algorithms computing SVD?

For example we have 2 algorithms from R: SVD and irlba and I want to compare them int terms of speed,memory and precision. But I don't understand how to compare output of algorithms, they must be ...
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1answer
35 views

predict category by using K-NN algorithm having text features

I would like to predict the category of the provided data by using K-NN algorithm. Here is an example of the training data set ...
2
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1answer
33 views

re-arrange elements in two vectors to minimize the elementwise difference between them

I have two vectors, $X$ and $Y$ of equal length $n$. Basically, I want to match up each value from $X$ with a value from $Y$, so that the sum of the differences between the two values per pair is as ...
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36 views

In CHAID, shouldn't we merge categories when p<alpha rather than p>alpha?

In CHAID, the categories are merged when P>alpha in the first step. BUT Since CHAID uses Chi-square statisitic, if p-value < alpha, we reject the null ( Independence), hence, meaning the ...
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1answer
96 views

Anomaly detection using exponential weighted moving average

I would like to detect anomaly using exponential weighted moving average. I don't have series of data points. All I have is EMA(t-1) and the data point of the current time(t) DP(t). From these data, ...
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1answer
23 views

Simple approximation of tail surprisal of poisson distribution

I want to determine (in an algorithm) the approximate surprisal of getting an outcome "as extreme as $k$" from the $Poisson(\lambda)$ distribution. My original plan was to use ...
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27 views

Anomaly detection for one feature vector

I have a $n$-dimensional vector of ordered multiple testing $p$-values and I would like to reject the first values that are under a certain threshold $\alpha$. I am looking at this problem as an ...
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2answers
73 views

What statistics algorithm should be used to identify why something is increasing?

I work at a hospital and have been asked to use statistical algorithms to identify an increase in Census which is really the number of patient days in a hospital. It has trended up about 15 percent in ...
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1answer
80 views

Efficient solution of fmincg without providing gradient?

I'm working on multiclass logistic regression model with a large number of features (numFeatures>100). Using a maximum likelihood estimation-based cost function and ...
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1answer
49 views

Which machine learning algorithm is the slowest BUT surest?

CrossPost: https://stackoverflow.com/questions/24301743/which-machine-learning-algorithm-is-the-slowest-but-surest?noredirect=1#comment37556042_24301743 Perhaps my perception of time is augmented by ...
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1answer
534 views

Steps done in factor analysis compared to steps done in PCA

I know basically how to express PCA (Principal component analysis) mathematicaly, but I would like to know steps that should be used for factor analysis. ...
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0answers
25 views

Association Rules “with a kind of class”

I want to use/adapt a recommendation algorithm for posters in an e-commerce. The thing is that I want to use previous categories searched before posting in a particular category (has to be at a very ...
2
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0answers
42 views

Iterative or Lazy Reservoir Sampling

I'm fairly well acquainted with using Reservoir Sampling to sample from a set of undetermined length in a single pass over the data. One limitation of this approach, in my mind, is that it still ...
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1answer
155 views

Clustering algorithms for extremely sparse data

I am trying to cluster an extremely sparse text corpus, and I know the number of clusters (my data is the title and author list of scientific publications, for which I already know the number of ...
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14 views

Fair Ranking of Ratings Based on Number of Votes

I'm attempting to take a list of products and rank them according to rating and votes. This is tricky! Lets suppose product A is rated at average 5.6 at 310 votes. Product B is average 7.3 at 10 ...