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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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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11 views

Algorithm questions [closed]

Hello I am Trying to build an multiple choice Examination system Through the use PHP/javaScript/Html Where in ITEM analysis is Present. Item In which DescribeL: How many got correct in this number ...
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1answer
18 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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20 views

I need the whole Lasso(Least Absolute Shrinkage and Selection Operator) Algorithm. Anyone?

Anyone could give me the whole Lasso Algorithm? The step by step procedure in determining Lasso solutions? I barely need this for my thesis. Thank You.
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36 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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41 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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42 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
28 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
148 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
110 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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25 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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53 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
32 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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145 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
26 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 ...
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11 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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30 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
68 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
19 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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26 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
70 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
38 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
46 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
300 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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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 ...
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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 ...
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1answer
90 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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12 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 ...
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14 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 ...
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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: ...
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2answers
50 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 ...
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2answers
292 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 ...
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3answers
97 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 ...
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1answer
47 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 ...
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2answers
179 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 ...
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1answer
96 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?
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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 ...
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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 = ...
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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 ...
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3answers
295 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
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1answer
97 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 ...
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1answer
54 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 ...
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1answer
121 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 ...
2
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1answer
42 views

Face Recognition approach DCT features

Face Recognition approach based on entropy estimate of the nonlinear DCT features proposes to use maximum entropy estimate of the DCT of the pixels. My question is maximizing entropy would mean ...
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23 views

A binomial random number generating algorithm that works when n*p is very small

I need to generate binomial random numbers: For example, consider binomial random numbers. A binomial random number is the number of heads in N tosses of a coin with probability p of a heads ...
3
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1answer
110 views

Machine learning classifiers big-O or complexity

To evaluate the performance a new classifier algorithm, I'm trying to compare the accuracy and the complexity (big-O in training and classifying). From Machine Learning: a review I get a complete ...
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43 views

Understand the parameters for multiple regression - question based on the notations in a given algorithm

I've set up a regression model but am not sure if I'm doing it right. I'm using multiple regression to help do multi-class classification. So far I feel like I've understood the theory, but I'm ...
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1answer
26 views

Algorihtm analysis with time complexity [closed]

We know that there are searching algorithms with time complexity O(lgn) but is there any sorting algorithm with time complexity O(lgn)?
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1answer
63 views

How to find log-likelihood of multiple sequences for hmm using Kevin Murphy toolkit for MATLAB

I have an observation sequence of TPM, EPM and prior. I want to find the log-likelihood of around 100 sequences of length 10 at a time. How can I do this using a forward algorithm?
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1answer
86 views

Uniform sampling of a set of weighted samples

Consider a two-stage sampling scheme: First, use weighted random selection from a list to obtain a set of N unique elements. Next, use uniform random selection to pick one of those elements. How can ...