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.

learn more… | top users | synonyms

1
vote
0answers
39 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
votes
0answers
13 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 ...
1
vote
0answers
28 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 ...
1
vote
0answers
6 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 ...
1
vote
0answers
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 ...
0
votes
0answers
46 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 ...
0
votes
0answers
20 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 ...
0
votes
2answers
21 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 ...
2
votes
2answers
52 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. ...
0
votes
0answers
15 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 ...
0
votes
1answer
22 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 ...
1
vote
0answers
38 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 ...
0
votes
0answers
61 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 ...
0
votes
0answers
44 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 ...
0
votes
1answer
29 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 ...
1
vote
3answers
182 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 ...
2
votes
3answers
130 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 ...
2
votes
0answers
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 ...
1
vote
0answers
66 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 "...
1
vote
1answer
33 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 ...
1
vote
2answers
153 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 ...
0
votes
1answer
28 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
votes
1answer
24 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 ...
1
vote
0answers
33 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 ...
0
votes
1answer
80 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, ...
0
votes
1answer
21 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 ...
0
votes
0answers
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 ...
1
vote
2answers
72 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 ...
1
vote
1answer
50 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 ...
-1
votes
1answer
48 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 ...
1
vote
1answer
383 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. ...
0
votes
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
votes
0answers
39 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 ...
1
vote
1answer
113 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 ...
0
votes
0answers
13 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 ...
1
vote
0answers
16 views

Prioritization based on three factors

Background: Sales reps visit doctor and detail about a product/drug. One visit is termed as one call. In return he writes the prescriptions to doctors prescribing that particular drug. Problem ...
2
votes
1answer
77 views

Finding all largest sequences

What would be a good / efficient algorithm or approach to find all the largest sequences within a list of chains with varying lengths? For instance these chains: ...
2
votes
2answers
53 views

Classification with mislabeled data

I have a classification dataset where roughly 20% (maybe more) of the labels are incorrect. There is no way to know which labels are incorrect and no way to eliminate them in the future when further ...
1
vote
2answers
398 views

K-medoid clustering in python

How do I implement k-medoid clustering algorithms like PAM and CLARA in python 2.7? I am currently using Anaconda, and working with ipython 2.7. I have tried scipy.clusters but they don't seem to ...
4
votes
3answers
110 views

Gradient descent based minimization algorithm that doesn't require initial guess to be near the global optimum

The problem with gradient descent algorithms, e.g. the Levenberg–Marquardt algorithm, is that they will converge into a minimum that is nearest to the initial guess, so when starting from different ...
0
votes
1answer
49 views

Smoothing Spline Example

I am learning the smoothing spline method. I saw that smoothing spline is a penalty term to reduce overfitting in linear regression. Given dataset {$(x_1,y_1),(x_2,y_2)..(x_n,y_n)$}So the formular ...
1
vote
2answers
251 views

How to reduce overfitting in linear regression

I am working with linear regression methods. The weakness of the method is the possibility of overfitting. So to reduce it, some papers use regularization. Are there other methods to reduce ...
3
votes
1answer
115 views

Benefits of CART over ID3 algorithm

When building decision trees over a dataset that generates nodes with bad purity, is there any benefit of using the CART algorithm over the iterative dichotomizer 3 (ID3) algorithm?
0
votes
0answers
10 views

Which algorithm to use with progressive levels and average probability per level?

I have some data about customers presented with offers and want to predict the probability of new samples (customers) buying a product (Success). I created a "feature" called ...
0
votes
2answers
32 views

which algorithm uses a multidimension array of average probabilities

Is there an algorithm that returns the mean probability of response from a multi-dimensional matrix? For example, if I have a set of features: customerClass = ...
0
votes
0answers
14 views

Estimating carryover constants

I am wondering how can I estimate $ \alpha $ in the following carryover recursive estimation: $ \lambda_i = \alpha_\lambda \cdot \lambda_{i-1} + (1-\alpha_\lambda) \cdot y_{i-1} $ I have read ...
3
votes
3answers
385 views

Anomaly detection: what algorithm to use?

Context: I'm developing a system that analyzes clinical data to filter out implausible data that might be typos. What I did so far: To quantify the plausibility, my attempt so far was to normalize ...
2
votes
1answer
111 views

What's the algorithm for finding sequences used by TraMineR?

I'm working an analysis about finding frequent sequences in a event-state dataset using the R package TraMineR (and ...
0
votes
1answer
60 views

Denormalizing Data

I am applying Polynomial Regression to my data, however the parameters theta were always =0, i noticed that my y data or output is too large in the order of 100000 so i normalized y, i got very good ...
3
votes
1answer
141 views

Evaluating matrix factorization algorithms for Netflix

I've been trying to implement Simon Funk's movie recommendation algorithm explained here. I understand how the user and item factors are computed. However the evaluation method is not clearly ...