Tagged Questions

0
votes
0answers
43 views

AIC vs BIC vs MDL

I am trying to learn the difference between the three approaches and their applications. a) As I understand, AIC = -LL+K BIC = -LL+(K*logN)/2 Unless I am ...
2
votes
1answer
46 views

Datamining and time series forecasting

Could we say time series forecasting is a part of data-mining or it's just a data-mining tool?
0
votes
2answers
180 views

Time series prediction - what is Autoregressive Tree model ? (Python)

Our problem: model evolution of values of a continuous variable over time. I came through a paper presenting an approach for predicting the next values for a time series. Whereas ARIMA model is more ...
3
votes
1answer
45 views

Methods for teasing apart the influence of different time series features on a target feature?

Are there any established methods for teasing apart the influence of different time series features on a target feature? To illustrate: The target: Sales volume of kittens. Features: Time of year, ...
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 ...
2
votes
0answers
30 views

What is the difference between emerging and discriminative patterns?

I'm working on a way to make efficient classification on sequential patterns mining algorithms. Looking in the state-of-the-art I found that there is two type of algorithm to address this problem : ...
1
vote
2answers
189 views

Temporal association rules with arulesSequences with quantities

I am trying to mine product-usage sequences for multiple users of online gaming site. I have found the R package arulesSequences but am not sure how to fit it to my problem. The data format would be ...
1
vote
1answer
252 views

Clustering of time series

I have a set of almost 1600 time series on 2 years which I want to group into clusters. Do you think this is possible using k-means? Which method do you advice me to use? Is this possible at all using ...
6
votes
0answers
155 views

Finding the correct data mining approach

(I apologise for being a newb, but I'm a researcher introducing myself to data mining---any help or insight would be greatly appreciated. Also, this isn't technically a homework question, but I've ...
1
vote
0answers
78 views

Modern and practical methods for forecasting time series cross section data

I have a data array $X$ which is of size $T \times N \times K$, where $T = 1500$, $N = 1500$ and $K = 10$. Physically, the 1st index $1, 2, \ldots, T$ denotes days, while the 2nd index $1, 2, ...
1
vote
3answers
312 views

Univariate clustering of time series

I just want to know if its possible to cluster an univariate time series, in order , say, to detect anomalies? and do you have any online version for denstream code, in Matlab? here is the time ...
3
votes
2answers
449 views

Pre-processing time series data for data mining / predictive modeling input

What are some ways to prepare/pre-process time series data to use the series data as a predictor(s) in a predictive model (classification or regression)? Specifically, what are the methods to be ...
2
votes
1answer
131 views

Multiple values in a timestamp

I am working with a time series (discrete) that has ideally 1 value per time stamp. In some cases, we are seeing multiples that have a wide range all recorded with the same time stamp. Up to now, we ...
5
votes
3answers
834 views

Outliers spotting in time series analysis, should I pre-process data or not?

My question builds on a previous post on outlier detection in generic time series, and specifically on the answer provided by the always great Rob H. I work for a small-sized manufacturing company ...
2
votes
1answer
151 views

Time series digitization

I am looking for a viable method to create an alphabet out of multidimensional time series data. My intention is to use pattern/string matching algorithms (potentially genetic) to find profitable ...
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 ...
2
votes
0answers
62 views

Determine optimal (recurring) frequency of discrete values

So I'm trying to determine a semi-efficient way to calculate the optimal (recurring) frequency of a set of data. The data only exists at random time periods, but it is assumed that the data set is ...
0
votes
2answers
169 views

Ways of finding associations in time series

I am trying to develop a logic to identify association between different time series for association mining. I have a lot of series and need to find whether or not the association exists. I figured ...
2
votes
1answer
1k views

Sliding window validation for time series

I have a broad question about sliding window validation. Specifically, I am looking at using Rapid Miner to predict future values of a financial series using "lagged" values of that series and other ...
35
votes
4answers
1k views

Do we have a problem of “pity upvotes”?

I know, this may sound like it is off-topic, but hear me out. At Stack Overflow and here we get votes on posts, this is all stored in a tabular form. E.g.: post id voter id vote type ...
10
votes
6answers
458 views

Dubious use of signal processing principles to identify a trend

I am proposing to try and find a trend in some very noisy long term data. The data is basically weekly measurements of something which moved about 5mm over a period of about 8 months. The data is to ...