4
votes
2answers
182 views

Data mining techniques in R for advertising and sales data

I would like to apply one or more data mining techniques to a dataset, in order to see the effect advertising has on sales. I am working from this dataset. It has 36 consecutive entries of monthly ...
0
votes
0answers
23 views

Literature for prediction models where each training example has a different amount of data?

This could be a machine learning question as much as a statistics question, but I think this is the best place to put the question. Here are three different examples of problems where each ...
0
votes
1answer
42 views

How to find which time series is trending more?

Let us say I have two sets of time varying series as shown below: ...
1
vote
0answers
28 views

How to find the most important factors or combination of levels in a finite data set

I’d like to discover which “calendar factors” (e.g. day of the week, month) have the strongest relationship with whether or not a particular product is sold at least once. For days when the product ...
0
votes
0answers
34 views

Data mining of time series

I have a dataset which consist of n time series variables $X_1$..$X_n$ , and a time serie output $Y$. I would like to mine the data to find if some functions (lagged or not) of the $X_i$ can predict ...
0
votes
0answers
46 views

Time Period Predictive Modeling

I have been implementing some classification algorithms (Naive Bayes, SVM etc) recently on the iris data sets to get head start into the data science field. I enjoy working on machine learning ...
0
votes
0answers
42 views

Gather insights from quarterly financial forecast data

I am trying to analyze a quite large (~25,000 rows) dataset of financial forecasts. The forecasts are usually not derived from algorithms, but come from a large number of analysts who forecast the ...
5
votes
2answers
156 views

Ordinal/continuous vs dummy variable for time series regression/data mining

Let's suppose I have a time series data that I would like to regress $y$ on $x$ and $Time$. See below for the dataset. ...
1
vote
1answer
50 views

The concept of “average run length” in change point detection

With respect to the change point detection for data stream, there is a concept of "average run length", which is discussed in the CPM package manual: I am not clear why that "average number of ...
5
votes
2answers
173 views

What to do with my data?

I'm quite new here so please excuse me if this isn't a suitable question. I'm developing a site for students to allow them to upload their virtual transcripts (grade report) to our site and allow us ...
0
votes
0answers
30 views

Comparing Twitter Trends on a Monthly Basis?

I'm trying to compare the frequency of a keyword is mentioned on Twitter in a monthly basis (e.g.: how many times the keyword "MissWorld" appears on September, how many it appears on August, how many ...
0
votes
0answers
42 views

Finding motif in an on-line (real time) time series

I have a data stream (one integer value per second): 480, 481, 479, 482,... If I show these values in a 2D-diagram, I have something like (for limited values): ...
0
votes
0answers
40 views

Transform a daily closed values to data of rolling annual returns.

My problem is that : I have the daily closed values of the initial index for DJUSER, MSCI, SP500, SPGSCI from 1 January 1999 to 31 December 2011. I want to transform them in to data of rolling annual ...
1
vote
0answers
99 views

Features selection by filter methods for multivariate time series

I have a data set in which the samples are multivariate (about 30 variable/features) time series. These samples refer to two classes. I would like to select the variables more relevant to discriminate ...
0
votes
0answers
46 views

Help with Algorithm Selection

I have asked this on the rapid-miner forum (http://forum.rapid-i.com/) but it can't hurt to get other opinions due to it not being a software-specific question. If this is the wrong section please let ...
1
vote
1answer
114 views

How to improve forecasting accuracy?

I got some users' history data and generated some sequences of real numbers. The length of each sequence is between 15 and 25. What's more, I do not know whether these sequences have patterns and the ...
0
votes
0answers
171 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
61 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
540 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
56 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
192 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 ...
3
votes
1answer
47 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
409 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
448 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
1answer
258 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
113 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, ...
3
votes
3answers
518 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 ...
4
votes
2answers
739 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
187 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
1k 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
158 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
995 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
69 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
190 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
2k 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 ...
38
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
503 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 ...