refers to a statistical procedure that can be updated as a sequence of data arrive.
0
votes
0answers
28 views
Sample changing distribution
I have the following process:
I have N buckets in front of me, $M$ of which are filled with water (the other ones are empty).
I pick one of them (consider uniform distribution) and empty it (so ...
1
vote
1answer
76 views
Training Hidden Markov Models for multiple input observations
I'm working with Hidden Markov Models and I have a dataset composed by independent phrases, where each word is an observation. Hence, the best way to adjust my parameters (via Baum-Welch algorithm) is ...
0
votes
0answers
45 views
Online Linear Regression with updates on past information
Suppose we have the following algorithm
An online linear regression algorithm implemented using gradient descent. The step rate $\alpha$ is calculated using something that correlates to the squared ...
1
vote
0answers
38 views
R packages for ONLINE seasonality analysis
First please note that this question is NOT a duplicate of R packages for seasonality analysis.
What is the best way to remove seasonality on a edge? The usual methods have all huge edge effects. It ...
0
votes
0answers
25 views
Gibbs Sampling weight more recent samples heavier?
I'm implementing an online Albert and Chib Gibbs sampler for Probit regression (see http://www.cs.ubc.ca/~emtiyaz/Writings/EMTstatisticalcomputation.pdf or ...
4
votes
2answers
179 views
Time series forecasting lookback windows — sliding or growing?
Are there any good reasons to prefer a sliding model training window to a growing window in online time series forecasting (or vice versa)? I'm particularly referring to financial time series.
I ...
0
votes
0answers
23 views
Agregating results of a classifier (model) trained online with different parameter values
Is there any work about training online many instances of the same classifier simultaneously with different parameter settings, in order to have a better classification accuracy ? It is somehow like ...
0
votes
0answers
39 views
Online algorithm to compute variance with a decay
Could somebody point me to an online algorithm that computes the variance, but gives a higher weight to more recent values?
1
vote
0answers
97 views
Online algorithm for computing variance of complex numbers [closed]
I was wondering if there is an online algorithm like Welford 1962 algorithm exists for computing the variance of complex numbers.
Check these links for more information:
Accurately computing running ...
3
votes
0answers
77 views
Reference for implementing generalized likelihood ratio test to determine online whether time-series mean has shifted
What is a reference that describes the "generalized likelihood ratio" test to determine online (i.e., meaning that we add an observation, then check, then add an observation, then check) whether the ...
2
votes
2answers
114 views
Choosing which data-point to label (active learning)
For an online unsupervised learning algorithm, data-points are learned sequentially. The performance may improve if in addition to the unlabelled data we have some labelled data-points (i.e. ...
-1
votes
1answer
136 views
An incremental Gaussian mixture model
Question 1:
Suppose that data is modelled by a mixture of K probability distributions which are actually Gaussians. $P(x_i|\theta_j)$ is the probability density of the j'th cluster, for which the ...
0
votes
1answer
73 views
Document image analysis and retrieval with online incremental clustering
Is there any interesting problem in the area of "Document Image Analysis and Retrieval" which by nature needs an online/incremental clustering process ? The problem may be in the context of "Logical ...
0
votes
1answer
97 views
Continuously depending a binary random variable
Suppose I have 2 exclusive events, and at each point in time, I maintain the probability for the first event, p (the other one being 1-p). There is online, streaming information arriving all the time, ...
0
votes
2answers
114 views
How do I model time to an event with online data?
I am looking at streaming data (i.e. online model), and looking for a specific discrete event. I want to stochastically model the time until this even happens, or if easier, say, model the probability ...
4
votes
5answers
387 views
How to handle online time series forecast?
I have been dealing with the following problem. I have kind of a real time system and every time frame I read its current value, creating a time series (such as 1, 12, 2, 3, 5, 9, 1, ...). I'd like to ...
2
votes
2answers
99 views
3
votes
1answer
231 views
Simple random walk and sudden drift, how to detect the change?
I have got the following question relating to random walks. I would like to determine the moment when a random walk changes from being a simple random walk to start to drift at certain time. This sort ...
2
votes
0answers
298 views
Distance threshold for clustering
Usually online clustering methods (based on kmeans or not) define a distance threshold value. If a new data-point $x$ is far enough from the nearest center $c$ (i.e. the distance from $x$ to $c$ is ...
0
votes
0answers
39 views
Where can I get some case studies (books, forums) regarding online voting mechanics? [closed]
I have been looking all over but I still can't find a place
with good information on online voting mechanics and case studies.
I'm looking for information like what to do to avoid cheating, how
many ...
5
votes
1answer
107 views
Techniques for incremental online learning of classifier on stream data
Which may be good techniques to face this abstract problem?
You have a data stream of a continuous signal, as one from a physical sensor. That signal has real (discretized) values, no attribute; ...
4
votes
2answers
256 views
On-line detection of over-fitting in neural networks
As we train a neural network, we have access to the error-rate (both on training, and test patterns). What are standard techniques to use this information to stop the learning as quickly as possible ...
2
votes
2answers
152 views
Finding communities in online social networks by removing nodes
I want to carry out Graph Clustering in a huge undirected graph with millions of edges and nodes. Graph is almost clustered with different clusters joined together only by some nodes (kind of ...
2
votes
0answers
116 views
Incremental learning methods in R
I am looking for some libraries in R that can do incremental learning (also called online or sequential learning). The use case of such learning in comparison to traditional batch methods would be to ...
1
vote
1answer
171 views
clustering with particle filters
Suppose we want to cluster a data stream of unknown number of clusters, and estimate them using particle filters. With particle filters, we need to know $P(x_t | x_{t-1})$ and $P(z_t | x_t)$ (where z ...
1
vote
1answer
64 views
Is there a sequential version of probabilistic latent semantic analysis?
Does someone know if it exists some way to do online learning with pLSA? The model training is really time consuming, so it is not feasible to rebuild it after every changes in the data.
2
votes
1answer
220 views
Sequential clustering with an unknown number of clusters
Is there any clustering algorithms that:
does not assume the number of clusters to be known, and
processes the data in only one pass by considering it as a continuously arriving data stream (and we ...
0
votes
0answers
192 views
Efficient method/technique to update covariance matrix
A covariance matrix of multivariate random variable can be constructed given a time-series random variables.
Eg. If you observe a student's performance in different objects (Math, English, Physics, ...
7
votes
2answers
597 views
Computation of new standard deviation using old standard deviation after change in dataset
I have an array of $n$ real values, which has mean $\mu_{old}$ and standard deviation $\sigma_{old}$. If an element of the array $x_i$ is replaced by another element $x_j$, then new mean will be
...
5
votes
2answers
194 views
How to perform Gaussian process regression when function being approximated changes over time?
What are good strategies for performing Gaussian process regression when the function I am trying to approximate changes over time? The naive approach that springs to my mind is to only use the N most ...
5
votes
2answers
184 views
Online clustering
I'm trying to build a K-means clustering system with 'online learing', that is, there are existing K clusters and data points in them, and periodically there is a new data point that is sent to an ...
7
votes
3answers
569 views
Are there algorithms for computing “running” linear or logistic regression parameters?
A paper "Accurately computing running variance" at http://www.johndcook.com/standard_deviation.html
shows how to compute running mean, variance and standard deviations.
Are there algorithms where the ...
1
vote
0answers
41 views
Incremental or Online or Single pass or Data Stream Clustering refers to the same thing? [duplicate]
Possible Duplicate:
Incremental or Online or Single pass or Data Stream Clustering refers to the same thing?
Incremental clustering algorithms
Online clustering algorithms
Data stream ...
0
votes
1answer
201 views
Incremental or online or single pass or data stream clustering refers to the same thing?
Incremental clustering algorithms
Online clustering algorithms
Data stream clustering algorithms
Single pass clustering algorithms
Are the following expressions related? Does some of them include ...
1
vote
2answers
258 views
Online fitting for normal distributions
I was wondering if there exist efficient online or dynamic algorithm for fitting a normal distribution to data as it comes in. I am interested in two variants:
The algorithm is fed data points one ...
1
vote
0answers
87 views
How to compute median in an online fashion? [duplicate]
Possible Duplicate:
What is a good algorithm for estimating the median of a huge read-once data set?
Imagine you have a large, multivariate dataset that resides on disk.
Are there any ...
1
vote
1answer
69 views
Estimate variance of sub-sets from overall variance
I am looking for a way to estimate the variance of a summed sub-set based on the variance of those sums.
Si = sum( Ai )
S = { S0...Sn }
V = variance( S )
That ...
3
votes
2answers
244 views
Incremental PCA in R
I am looking for a R package that implements Incremental PCA (online version of PCA)
Is there anybody that knows a piece of code that implements such algorithm?
8
votes
4answers
371 views
Online outlier detection
I want to process automatically-segmented microscopy images to detect faulty images and/or faulty segmentations, as a part of a high-throughput imaging pipeline. There's a host of parameters that can ...
2
votes
1answer
117 views
Can you recommend an online survey platform for 5k+ participants?
I am planning to perform an online behavioral survey across a nationwide sample, and I expect several thousand responses. I expect to have not that many questions (perhaps 3 pages, 8 qs each), ...
4
votes
2answers
160 views
Online method for detecting wave amplitude
I would like to measure the amplitude of waves in a noisy time-series on-line. I have a time-series that models a noisy wave function, that undergoes shifts in amplitude. Say, for example, something ...
11
votes
1answer
215 views
Online, scalable statistical methods
This was inspired by Efficient online linear regression, which I found very interesting. Are there any texts or resources devoted to large-scale statistical computing, by which computing with ...
6
votes
2answers
889 views
Exponential weighted moving skewness/kurtosis
There are well-known on-line formulas for computing exponentially weighted moving averages and standard deviations of a process $(x_n)_{n=0,1,2,\dots}$. For the mean,
$\mu_n = (1-\alpha) \mu_{n-1} + ...
6
votes
1answer
850 views
What is the precise definition of a “Heywood Case”?
I had been using the term "Heywood Case" somewhat informally to refer to situations where an online, 'finite response' iteratively updated estimate of the variance became negative due to numerical ...
10
votes
5answers
1k views
Online algorithm for mean absolute deviation and large data set
I have a little problem that is making me freaking out.
I have to write procedure for an online acquisition process of a multivariate time series.
At every time interval (for example 1 second), I get ...
5
votes
1answer
228 views
Bias from increased information in FLAME clustering
I hope this is an appropriate forum for this question...if not, any pointers on a place to ask would be great. If my questions is not clear, please just let me know and I'll try to add ...
