Tagged Questions

0
votes
1answer
63 views

First steps learning to predict financial timeseries using machine learning

I am trying to get a grasp on how to use machine learning to predict financial timeseries 1 or more steps into the future. I have a financial timeseries with some descriptive data and I would like to ...
0
votes
2answers
46 views

Time Series Similarity : Differing Lengths with R

I am experimenting with creating a distance matrix between time series for clustering and similarity searching. The main reference I am using is for the Similarity procedure in SAS (Paper). I would ...
1
vote
1answer
52 views

Forecasting optimization techniques in fantasy baseball

I am currently trying to build a better forecasting model for my fantasy baseball roster. I currently am using commonly accepted projected season statistics (ZiPS from Fangraphs) to determine the ...
3
votes
0answers
37 views

Link Anomaly Detection in Temporal Network

I came across this paper that uses link anomaly detection to predict trending topics, and I found it incredibly intriguing: The paper is "Discovering Emerging Topics in Social Streams via Link Anomaly ...
2
votes
0answers
72 views

detecting circadian rhythm in a time series

I have a sensor that can detect minute changes in distance. It produces a time series. I would like to point it at people and detect things like their sleeping pattern. How would one build a system ...
0
votes
2answers
43 views

difference in training and testing procedure of model

Can anyone please tell me the difference in training and testing of a model. I have developed 5/6 different single pass online learning algorithm (ets, ets+, evolving fuzzy modelling, SOFNN, ...
0
votes
0answers
81 views

Predicting twitter activity using time series analysis

I'm interested to build a model for predicting how many tweets people I follow will probably tweet today (or by hour), based on their previous tweets in the last 60 days (or more). Of course that the ...
11
votes
1answer
267 views

How to predict one time-series from another time-series, if they are related

I have been trying to solve this problem for over a year without much progress. It is part of a research project I'm doing, but I will illustrate it with a story example I made up, because the actual ...
4
votes
2answers
170 views

Time series prediction with non-constant sampling interval

I have some data which can be modelled as such: each data sample $S$ is a series of discrete signal values $S(t_n) \in \{-1, 1\}$ measured at times $(t_{n, S})_{1 \leq n \leq N_S}$. The number of ...
1
vote
1answer
615 views

Example of time series prediction using neural networks in R

Anyone's got a quick short educational example how to use Neural Networks (nnet in R for example) for the purpose of prediction? Here is an example, in R, of a time series ...
2
votes
0answers
112 views

Anomaly detection in user behaviour using hidden Markov models

I would like to detect user anomalies or mal-behavior on a web site. For each user I monitor the web browser used, IP (and thus ISP & geo-location) of the user as well as users' activities on the ...
4
votes
2answers
186 views

How can I transform time series data so I can use simpler techniques for fault prediction?

I know this is primarily a statistics site, so if I am off-topic, please redirect me. I have a system with pumps that sometimes break and need to be replaced. I would like to be able to predict the ...
2
votes
1answer
115 views

Modelling longitudinal data

We have longitudinal data on children(n<20) in which we measure different quantities A,B,C,D (like distance walked, time spent in school etc.). These are all continuous variables. We measure these ...
0
votes
2answers
211 views

Predicting time series with NNs: should the data set be shuffled?

Suppose I'm trying to predict time series with a neural network. The data set is created from a single column of temporal data, where the inputs of each pattern are ...
0
votes
0answers
104 views

Where can I find airline ticket prices datasets? [closed]

I am looking for statistics on international flight ticket prices that contains the departure city and the arrival city, the date of purchase and the departure date. The reason for this is that I want ...
4
votes
5answers
385 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 ...
5
votes
3answers
365 views

Is it necessary to detrend and decycle time-series data when using machine learning methods?

For example: I want to forecast future values of a time-series based on previous values of multiple time-series' using a ANN and/or SVM. Inputs will be lagged values from each time series, and the ...
1
vote
0answers
133 views

Gaussian process - dimensionality reduction

Specific question on Gaussian Processes and dimensionality reduction. I saw a a method for dimensionality reduction for the squared exponential covariance function (not ARD) whereby one uses a GxD ...
3
votes
4answers
505 views

Time series analysis with neural networks

I'm new to neural networks and machine learning and I was wondering how you use time series data to set the weights of a regular FNN, and how you use the ending weights to forecast the time series. In ...
1
vote
0answers
117 views

How to compare the accuracy of two different models using statistical significance

I am working on time series prediction. I have two data sets $D1=\{x_1, x_2,....x_n\}$ and $D2=\{x_n+1, x_n+2, x_n+3,...., x_n+k\}$. I have three prediction models: $M1, M2, M3$. All of those model ...
1
vote
0answers
122 views

SVM and non-linear predictive models - feature selection

Just throwing out a general question. What do people think of applying feature selection methods when using SVMs to build predictive models? I understand that SVM have built in regularization with how ...
1
vote
0answers
86 views

What is the difference between tapped delay line and sliding window in a neural network?

I'm trying to model some time series data, and I've been reading about tapped delay line and sliding window to transform the input data. In my understanding a sliding window with windows size 1 ...
1
vote
1answer
204 views

Is the Dynamic Time Warping constraint Itakura Parallelogram based on series length?

I'm looking into the Itakura Parallelogram global constraint for Dynamic Time Warping. I am confused about the maximum width of the parallelogram, is it solely based on the length of the two time ...
2
votes
0answers
87 views

Classification of multiple time series and case level attributes

I'm pretty new to machine learning so wondering whether someone can help check my thinking or point me in the right direction! I need to create a classifier which can predict an outcome for a person ...
5
votes
0answers
141 views

Updating classification probability in logistic regression through time

I am building a predictive model that forecasts a student's probability of success at the end of a term. I’m specifically interested in whether the student succeeds or fails, where success is usually ...
3
votes
3answers
324 views

How to determine if a price decrease is historically significant?

I am creating a program to collect and analyze prices for goods and alert the user when the price decreases so that they can buy it on "sale." I know a little statistics (e.g. standard deviation) but ...
1
vote
1answer
126 views

Bucketising time series

I have a time series where the x-axis represents hour of the day and the y-axis represents the avgerage value of some variable, say speed of all the cars in New York. I want to bucketise this data (or ...
1
vote
1answer
120 views

Algorithms for predicting a couple points in the future

I'm familiar with supervised learning algorithms like regression and neural networks which look at a bunch of input points and learn a function which outputs a value (the value varying depending on ...
4
votes
1answer
641 views

Best practices for measuring and avoiding overfitting?

I am developing automated trading systems for the stock market. The big challenge has been overfitting. Can your recommend some resources describing methods for measuring and avoiding overfitting? I ...
9
votes
2answers
2k views

Support vector regression for multivariate time series prediction

Has anyone attempted time series prediction using support vector regression? I understand support vector machines and partially understand support vector regression, but I don't understand how they ...
7
votes
2answers
394 views

Machine learning techniques for time series estimation - forecasting price

Can anyone recommend any machine learning techniques for time series estimation? I have a series of times $t_{1}...t_{n}$, each having a set of associated features $f_{1}...f_{m}$, and a value $x$. ...
4
votes
2answers
111 views

Machine learning for activity streams

My data takes the form of a stream of events for each customer in my sample. For a given customer, the stream takes the form of a list of events over time: At T1, customer C1 bought 1 unit of ...
4
votes
5answers
537 views

Testing for stability in a time-series

Is there a standard (or best) method for testing when a given time-series has stabilized? Some motivation I have a stochastic dynamic system that outputs a value $x_t$ at each time step $t \in ...
13
votes
2answers
1k views

Proper way of using recurrent neural network for time series analysis

Recurrent neural networks differ from "regular" ones by the fact that they have a "memory" layer. Due to this layer, recurrent NN's are supposed to be useful in time series modelling. However, I'm not ...
5
votes
1answer
441 views

Ordering of time series for machine learning

After reading one of the "Research tips" of R.J. Hyndman about cross-validation and time series, I came back to an old question of mine that I'll try to formulate here. The idea is that in ...
1
vote
1answer
114 views

For data similar to audio, how to determine if there are 1 or 2 categories? [closed]

I have to compare pairs of audio strems as 1d time series. Looking at the aligned trajectories I need to either cluster them together or assume they arise from independent generators. I remember ...
10
votes
5answers
1k views

SVD dimensionality reduction for time series of different length

I am using Singular Value Decomposition as a dimensionality reduction technique. Given N vectors of dimension D, the idea is to ...