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KEEL - dataset     Time series data sets

In several domains as statistics, signal processing or econometrics, a time series is a sequence of data points, measured typically at successive times spaced at uniform time intervals. Time series data have a natural temporal ordering. This makes time series analysis distinct from other common data analysis problems, in which there is no natural ordering of the observations. A time series model will generally reflect the fact that observations close together in time will be more closely related than observations further apart. In addition, time series models will often make use of the natural one-way ordering of time so that values for a given period will be expressed as deriving in some way from past values, rather than from future values.

The data sets shown in this section represents time series problems. Consequently, the output value of these data sets is real valued.

Each data file has the following structure:

  • @relation: Name of the data set
  • @attribute: Description of an attribute (one for each attribute)
  • @inputs: List with the names of the input attributes
  • @output: List with the names of the output attributes
  • @data: Starting tag of the data

The rest of the file contains all the examples belonging to the data set, expressed in comma sepparated values format.

In the data sets, the first attribute (TimeStamp) does not appear in the @inputs. This is because that attribute is used to determine the position of each point in the series, but the model should not use it to predict the output value.


Below you can find all the Time series data sets available. For each data set, it is shown its name and its number of instances and attributes (Real/Integer/Nominal valued).

The table allows to download each data set in KEEL format (inside a ZIP file). It is possible to obtain the original data set obtained from the source repository where we have found it. Additionally, you can also download the data set already partitioned, by means of a 5-folds cross validation. These datasets have been used in several papers found in the literature, see for example:

J.D. Wichard. Forecasting the NN5 time series with hybrid models. International Journal of Forecasting, 27(3):700-707, 2011.

By clicking in the column headers, you can order the table by names (alphabetically), by the number of examples or attributes. Clicking again will sort the rows in reverse order.

Namedownarrow.png#Attributes (R/I/N)downarrowS.png#Examplesdownarrow.png Data set 5-fcv Original time series Header
NNGC1_dataset_E1_V1_0014        (4/0/0)370zip.gifzip.gifzip.giftxt.png
NNGC1_dataset_D1_V1_0034        (4/0/0)430zip.gifzip.gifzip.giftxt.png
NNGC1_dataset_D1_V1_0054        (4/0/0)430zip.gifzip.gifzip.giftxt.png
NNGC1_dataset_D1_V1_0084        (4/0/0)540zip.gifzip.gifzip.giftxt.png
NNGC1_dataset_D1_V1_0094        (4/0/0)540zip.gifzip.gifzip.giftxt.png
NNGC1_dataset_D1_V1_0044        (4/0/0)545zip.gifzip.gifzip.giftxt.png
NNGC1_dataset_D1_V1_0104        (4/0/0)585zip.gifzip.gifzip.giftxt.png
NNGC1_dataset_D1_V1_0064        (4/0/0)610zip.gifzip.gifzip.giftxt.png
NNGC1_dataset_D1_V1_0074        (4/0/0)610zip.gifzip.gifzip.giftxt.png
NNGC1_dataset_E1_V1_0104        (4/0/0)650zip.gifzip.gifzip.giftxt.png
NNGC1_dataset_E1_V1_0084        (4/0/0)740zip.gifzip.gifzip.giftxt.png
NNGC1_dataset_E1_V1_0094        (4/0/0)740zip.gifzip.gifzip.giftxt.png
NN5_Complete_1104        (4/0/0)782zip.gifzip.gifzip.giftxt.png
NN5_Complete_1114        (4/0/0)782zip.gifzip.gifzip.giftxt.png
NN5_Complete_1094        (4/0/0)782zip.gifzip.gifzip.giftxt.png
NN5_Complete_1084        (4/0/0)782zip.gifzip.gifzip.giftxt.png
NN5_Complete_1074        (4/0/0)782zip.gifzip.gifzip.giftxt.png
NN5_Complete_1064        (4/0/0)782zip.gifzip.gifzip.giftxt.png
NN5_Complete_1054        (4/0/0)782zip.gifzip.gifzip.giftxt.png
NN5_Complete_1044        (4/0/0)782zip.gifzip.gifzip.giftxt.png
NN5_Complete_1034        (4/0/0)782zip.gifzip.gifzip.giftxt.png
NN5_Complete_1024        (4/0/0)782zip.gifzip.gifzip.giftxt.png
NN5_Complete_1014        (4/0/0)782zip.gifzip.gifzip.giftxt.png
NNGC1_dataset_F1_V1_0074        (4/0/0)895zip.gifzip.gifzip.giftxt.png
NNGC1_dataset_F1_V1_0084        (4/0/0)895zip.gifzip.gifzip.giftxt.png
NNGC1_dataset_F1_V1_0094        (4/0/0)895zip.gifzip.gifzip.giftxt.png
NNGC1_dataset_F1_V1_0104        (4/0/0)895zip.gifzip.gifzip.giftxt.png
NNGC1_dataset_F1_V1_0114        (4/0/0)895zip.gifzip.gifzip.giftxt.png
NNGC1_dataset_F1_V1_0014        (4/0/0)965zip.gifzip.gifzip.giftxt.png
NNGC1_dataset_F1_V1_0024        (4/0/0)1020zip.gifzip.gifzip.giftxt.png
NNGC1_dataset_D1_V1_0024        (4/0/0)1175zip.gifzip.gifzip.giftxt.png
Edat_1_16614        (4/0/0)1655zip.gifzip.gifzip.giftxt.png
NNGC1_dataset_F1_V1_0034        (4/0/0)1735zip.gifzip.gifzip.giftxt.png
NNGC1_dataset_F1_V1_0044        (4/0/0)1735zip.gifzip.gifzip.giftxt.png
NNGC1_dataset_F1_V1_0054        (4/0/0)1735zip.gifzip.gifzip.giftxt.png
NNGC1_dataset_F1_V1_0064        (4/0/0)1735zip.gifzip.gifzip.giftxt.png
Acont_1_20004        (4/0/0)1995zip.gifzip.gifzip.giftxt.png
B1dat_1_20004        (4/0/0)1995zip.gifzip.gifzip.giftxt.png
B1dat_2_20004        (4/0/0)1995zip.gifzip.gifzip.giftxt.png
D1dat_1_20004        (4/0/0)1995zip.gifzip.gifzip.giftxt.png
All data sets zip.gif

Collecting Data Sets

If you have some example data sets and you would like to share them with the rest of the research community by means of this page, please be so kind as to send your data to the Webmaster Team with the following information:

  • People answerable for the data (full name, affiliation, e-mail, web page, ...).
  • training and test data sets considered, preferably in ASCII format.
  • A brief description of the application.
  • References where it is used.
  • Results obtained by the methods proposed by the authors or used for comparison.
  • Type of experiment developed.
  • Any additional useful information.

Collecting Results

If you have applied your methods to some of the problems presented here we will be glad of showing your results in this page. Please be so kind as to send the following information to Webmaster Team:

  • Name of the application considered and type of experiment developed.
  • Results obtained by the methods proposed by the authors or used for comparison.
  • References where the results are shown.
  • Any additional useful information.

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