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Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
726 runs0 likes9 downloads9 reach6 impact
576 instances - 12 features - 2 classes - 0 missing values
No data.
726 runs0 likes9 downloads9 reach5 impact
36 instances - 30 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
723 runs0 likes4 downloads4 reach6 impact
418 instances - 19 features - 2 classes - 1239 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
723 runs0 likes6 downloads6 reach6 impact
366 instances - 35 features - 2 classes - 8 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
722 runs0 likes5 downloads5 reach6 impact
285 instances - 8 features - 2 classes - 27 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
722 runs0 likes6 downloads6 reach6 impact
683 instances - 36 features - 2 classes - 2337 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
721 runs0 likes5 downloads5 reach5 impact
34 instances - 9 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
721 runs0 likes5 downloads5 reach5 impact
60 instances - 8 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
721 runs0 likes5 downloads5 reach6 impact
226 instances - 70 features - 2 classes - 317 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
720 runs0 likes6 downloads6 reach6 impact
159 instances - 10 features - 2 classes - 6 missing values
Contains 110 data sets from the book 'The Statistical Sleuth' by Fred Ramsey and Dan Schafer; Duxbury Press, 1997. (schafer@stat.orst.edu) [14/Oct/97] (172k) Note: description taken from this web…
720 runs0 likes6 downloads6 reach5 impact
60 instances - 8 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
720 runs0 likes8 downloads8 reach6 impact
506 instances - 21 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
718 runs0 likes6 downloads6 reach6 impact
406 instances - 9 features - 2 classes - 14 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
718 runs0 likes6 downloads6 reach6 impact
159 instances - 16 features - 2 classes - 0 missing values
No data.
718 runs0 likes5 downloads5 reach5 impact
63 instances - 30 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
717 runs0 likes5 downloads5 reach6 impact
303 instances - 14 features - 2 classes - 7 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
717 runs0 likes5 downloads5 reach5 impact
90 instances - 9 features - 2 classes - 3 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
716 runs0 likes5 downloads5 reach6 impact
412 instances - 9 features - 2 classes - 96 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
714 runs0 likes4 downloads4 reach6 impact
303 instances - 14 features - 2 classes - 6 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
712 runs0 likes8 downloads8 reach6 impact
898 instances - 39 features - 2 classes - 22175 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
708 runs0 likes4 downloads4 reach7 impact
286 instances - 10 features - 2 classes - 9 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
708 runs0 likes5 downloads5 reach6 impact
365 instances - 4 features - 2 classes - 30 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
707 runs0 likes6 downloads6 reach6 impact
205 instances - 26 features - 2 classes - 57 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
707 runs0 likes8 downloads8 reach5 impact
48 instances - 5 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
707 runs0 likes5 downloads5 reach5 impact
52 instances - 25 features - 2 classes - 7 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
706 runs0 likes5 downloads5 reach5 impact
62 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
705 runs0 likes5 downloads5 reach6 impact
398 instances - 8 features - 2 classes - 6 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
705 runs0 likes6 downloads6 reach5 impact
96 instances - 5 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
701 runs0 likes3 downloads3 reach6 impact
736 instances - 20 features - 2 classes - 448 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
701 runs0 likes6 downloads6 reach5 impact
44 instances - 4 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
700 runs0 likes4 downloads4 reach6 impact
294 instances - 14 features - 2 classes - 782 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
700 runs0 likes5 downloads5 reach5 impact
67 instances - 16 features - 2 classes - 0 missing values
analcatdata A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission consists of a zip file containing two…
698 runs0 likes6 downloads6 reach5 impact
97 instances - 11 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
698 runs0 likes5 downloads5 reach5 impact
36 instances - 23 features - 2 classes - 0 missing values
No data.
697 runs0 likes5 downloads5 reach5 impact
89 instances - 9 features - 2 classes - 0 missing values
No data.
697 runs0 likes7 downloads7 reach6 impact
320 instances - 9 features - 2 classes - 0 missing values
analcatdata A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission consists of a zip file containing two…
692 runs0 likes6 downloads6 reach5 impact
83 instances - 4 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
691 runs0 likes5 downloads5 reach6 impact
528 instances - 22 features - 2 classes - 504 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
688 runs0 likes4 downloads4 reach5 impact
294 instances - 14 features - 2 classes - 782 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
687 runs0 likes5 downloads5 reach5 impact
52 instances - 24 features - 2 classes - 39 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
686 runs0 likes5 downloads5 reach6 impact
782 instances - 9 features - 2 classes - 466 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
683 runs0 likes5 downloads5 reach5 impact
60 instances - 11 features - 2 classes - 14 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
680 runs0 likes5 downloads5 reach6 impact
1945 instances - 19 features - 2 classes - 1133 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
676 runs0 likes13 downloads13 reach6 impact
10992 instances - 17 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
672 runs0 likes4 downloads4 reach6 impact
158 instances - 8 features - 2 classes - 87 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
670 runs0 likes4 downloads4 reach5 impact
62 instances - 8 features - 2 classes - 8 missing values
Contains 110 data sets from the book 'The Statistical Sleuth' by Fred Ramsey and Dan Schafer; Duxbury Press, 1997. (schafer@stat.orst.edu) [14/Oct/97] (172k) Note: description taken from this web…
668 runs0 likes6 downloads6 reach5 impact
87 instances - 11 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
653 runs0 likes10 downloads10 reach6 impact
1000 instances - 11 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
652 runs0 likes15 downloads15 reach6 impact
12960 instances - 9 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
646 runs0 likes9 downloads9 reach6 impact
1000 instances - 51 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
643 runs0 likes8 downloads8 reach6 impact
1000 instances - 11 features - 2 classes - 0 missing values
Datasets for `Pattern Recognition and Neural Networks' by B.D. Ripley ===================================================================== Cambridge University Press (1996) ISBN 0-521-46086-7 The…
640 runs0 likes6 downloads6 reach5 impact
214 instances - 10 features - 6 classes - 0 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
639 runs0 likes12 downloads12 reach6 impact
20000 instances - 17 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
638 runs0 likes9 downloads9 reach6 impact
1000 instances - 26 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
636 runs0 likes8 downloads8 reach6 impact
1000 instances - 51 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
631 runs0 likes7 downloads7 reach6 impact
1000 instances - 6 features - 2 classes - 0 missing values
DATA-SETS FROM DIGGLE, P.J. (1990). TIME SERIES : A BIOSTATISTICAL INTRODUCTION. Oxford University Press. Table: Table A2 Wool prices Information about the dataset CLASSTYPE: numeric CLASSINDEX: none…
626 runs0 likes6 downloads6 reach5 impact
310 instances - 9 features - 9 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
625 runs0 likes10 downloads10 reach6 impact
1000 instances - 11 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
624 runs0 likes8 downloads8 reach6 impact
1000 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
624 runs0 likes10 downloads10 reach6 impact
15000 instances - 49 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
622 runs0 likes5 downloads5 reach7 impact
10108 instances - 69 features - 2 classes - 2699 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
621 runs0 likes8 downloads8 reach6 impact
1000 instances - 51 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
620 runs0 likes10 downloads10 reach6 impact
1000 instances - 51 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
618 runs0 likes11 downloads11 reach6 impact
40768 instances - 11 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
617 runs0 likes10 downloads10 reach6 impact
1000 instances - 26 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
616 runs0 likes11 downloads11 reach6 impact
16599 instances - 19 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
615 runs0 likes9 downloads9 reach6 impact
1000 instances - 11 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
614 runs0 likes9 downloads9 reach6 impact
1000 instances - 51 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
608 runs0 likes9 downloads9 reach6 impact
1000 instances - 26 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
608 runs1 likes9 downloads10 reach6 impact
1000 instances - 26 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
604 runs0 likes9 downloads9 reach6 impact
1000 instances - 26 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
604 runs0 likes13 downloads13 reach6 impact
22784 instances - 17 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
602 runs0 likes12 downloads12 reach6 impact
13750 instances - 41 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
600 runs0 likes11 downloads11 reach6 impact
1000 instances - 101 features - 2 classes - 0 missing values
Data Sets for 'Regression Models for Time Series Analysis' by B. Kedem and K. Fokianos, Wiley 2002. Submitted by Kostas Fokianos (fokianos@ucy.ac.cy) [8/Nov/02] (176k) Note: - attribute names were…
599 runs0 likes10 downloads10 reach5 impact
1024 instances - 3 features - 4 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
598 runs0 likes8 downloads8 reach6 impact
1000 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
594 runs0 likes8 downloads8 reach6 impact
1000 instances - 6 features - 2 classes - 0 missing values
Datasets of Data And Story Library, project illustrating use of basic statistic methods, converted to arff format by Hakan Kjellerstrand. Source: TunedIT: http://tunedit.org/repo/DASL DASL file…
593 runs0 likes6 downloads6 reach5 impact
478 instances - 11 features - 3 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
589 runs0 likes11 downloads11 reach6 impact
22784 instances - 9 features - 2 classes - 0 missing values
Dataset from `Pattern Recognition and Neural Networks' by B.D. Ripley. Cambridge University Press (1996) ISBN 0-521-46086-7 The background to the datasets is described in section 1.4; this file…
587 runs0 likes5 downloads5 reach5 impact
61 instances - 19 features - 4 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
581 runs0 likes10 downloads10 reach6 impact
20640 instances - 9 features - 2 classes - 0 missing values
analcatdata A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission consists of a zip file containing two…
581 runs0 likes5 downloads5 reach5 impact
400 instances - 6 features - 4 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
575 runs0 likes9 downloads9 reach6 impact
1000 instances - 11 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
570 runs0 likes6 downloads6 reach5 impact
100 instances - 4 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
567 runs0 likes12 downloads12 reach6 impact
40768 instances - 11 features - 2 classes - 0 missing values
Fast training of support vector machines using sequential minimal optimization. In Bernhard Schölkopf, Christopher J. C. Burges, and Alexander J. Smola, editors, Advances in Kernel Methods - Support…
564 runs0 likes11 downloads11 reach14 impact
36974 instances - 124 features - 2 classes - 0 missing values
CODING: ITEM 1 = BUSINESS CONDIDIONS 6 MONTHS FROM NOW (CONFERENCE BOARD) ITEM 2 = JOBS 6 MONTHS FROM NOW (CONFERENCE BOARD) ITEM 3 = FAMILY INCOME 6 MONTHS FROM NOW (CONFERENCE BOARD) ITEM 4 =…
560 runs0 likes4 downloads4 reach5 impact
72 instances - 4 features - 6 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
554 runs0 likes9 downloads9 reach6 impact
40768 instances - 11 features - 2 classes - 0 missing values
Datasets from the Agnostic Learning vs. Prior Knowledge Challenge (http://www.agnostic.inf.ethz.ch) Dataset from: http://www.agnostic.inf.ethz.ch/datasets.php Modified by TunedIT (converted to ARFF…
548 runs0 likes9 downloads9 reach7 impact
3468 instances - 785 features - 2 classes - 0 missing values
analcatdata A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission consists of a zip file containing two…
537 runs0 likes4 downloads4 reach5 impact
285 instances - 8 features - 7 classes - 27 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
512 runs0 likes7 downloads7 reach5 impact
130 instances - 4 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
511 runs0 likes5 downloads5 reach6 impact
185 instances - 4 features - 2 classes - 0 missing values
No data.
496 runs0 likes6 downloads6 reach11 impact
45 instances - 4027 features - 2 classes - 5948 missing values
analcatdata A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission consists of a zip file containing two…
491 runs0 likes4 downloads4 reach4 impact
364 instances - 33 features - 6 classes - 101 missing values
Datasets from the Agnostic Learning vs. Prior Knowledge Challenge (http://www.agnostic.inf.ethz.ch) Dataset from: http://www.agnostic.inf.ethz.ch/datasets.php Modified by TunedIT (converted to ARFF…
486 runs0 likes14 downloads14 reach7 impact
14395 instances - 109 features - 2 classes - 0 missing values
GISETTE is a handwritten digit recognition problem. The problem is to separate the highly confusable digits '4' and '9'. This dataset is one of five datasets of the NIPS 2003 feature selection…
466 runs0 likes51 downloads51 reach13 impact
7000 instances - 5001 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
453 runs0 likes5 downloads5 reach5 impact
108 instances - 5 features - 2 classes - 0 missing values
Source: David Gil, dgil '@' dtic.ua.es, Lucentia Research Group, Department of Computer Technology, University of Alicante Jose Luis Girela, girela '@' ua.es, Department of Biotechnology, University…
451 runs0 likes7 downloads7 reach4 impact
100 instances - 10 features - 2 classes - 0 missing values
Molecular Classification of Cancer: Class Discovery and Class Prediction by Gene Expression Monitoring. Science, VOL 286, pp. 531-537, 15 October 1999. Web supplement to the article T.R. Golub, D. K.…
449 runs0 likes12 downloads12 reach5 impact
72 instances - 7130 features - 2 classes - 0 missing values
Jarkko Salojarvi, Kai Puolamaki, Jaana Simola, Lauri Kovanen, Ilpo Kojo, Samuel Kaski. Inferring Relevance from Eye Movements: Feature Extraction. Helsinki University of Technology, Publications in…
440 runs0 likes9 downloads9 reach5 impact
10936 instances - 28 features - 3 classes - 0 missing values