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* Dataset Title: Volcanoes on Venus - JARtool experiment Data Set Experiment: D4 * Source: Michael C. Burl MS 126-347, JPL 4800 Oak Grove Drive Pasadena, CA 91109 (818) 393-5345 Michael.C.Burl '@'…
121 runs0 likes4 downloads4 reach7 impact
8654 instances - 4 features - 5 classes - 0 missing values
* Dataset Title: Volcanoes on Venus - JARtool experiment Data Set Experiment: E3 * Source: Michael C. Burl MS 126-347, JPL 4800 Oak Grove Drive Pasadena, CA 91109 (818) 393-5345 Michael.C.Burl '@'…
104 runs0 likes2 downloads2 reach7 impact
1277 instances - 4 features - 5 classes - 0 missing values
* Dataset Title: Volcanoes on Venus - JARtool experiment Data Set Experiment: A4 * Source: Michael C. Burl MS 126-347, JPL 4800 Oak Grove Drive Pasadena, CA 91109 (818) 393-5345 Michael.C.Burl '@'…
136 runs0 likes5 downloads5 reach7 impact
1515 instances - 4 features - 5 classes - 0 missing values
* Dataset Title: Volcanoes on Venus - JARtool experiment Data Set Experiment: E2 * Source: Michael C. Burl MS 126-347, JPL 4800 Oak Grove Drive Pasadena, CA 91109 (818) 393-5345 Michael.C.Burl '@'…
105 runs0 likes2 downloads2 reach7 impact
1080 instances - 4 features - 5 classes - 0 missing values
* Dataset Title: Volcanoes on Venus - JARtool experiment Data Set Experiment: A3 * Source: Michael C. Burl MS 126-347, JPL 4800 Oak Grove Drive Pasadena, CA 91109 (818) 393-5345 Michael.C.Burl '@'…
133 runs0 likes7 downloads7 reach7 impact
1521 instances - 4 features - 5 classes - 0 missing values
* Dataset Title: Volcanoes on Venus - JARtool experiment Data Set Experiment: E1 * Source: Michael C. Burl MS 126-347, JPL 4800 Oak Grove Drive Pasadena, CA 91109 (818) 393-5345 Michael.C.Burl '@'…
105 runs0 likes2 downloads2 reach7 impact
1183 instances - 4 features - 5 classes - 0 missing values
* Dataset Title: Volcanoes on Venus - JARtool experiment Data Set Experiment: B4 * Source: Michael C. Burl MS 126-347, JPL 4800 Oak Grove Drive Pasadena, CA 91109 (818) 393-5345 Michael.C.Burl '@'…
123 runs0 likes3 downloads3 reach7 impact
10190 instances - 4 features - 5 classes - 0 missing values
good
0 runs0 likes0 downloads0 reach0 impact
10 instances - 4 features - classes - 2 missing values
* Title: Skin Segmentation Data Set * Abstract: The Skin Segmentation dataset is constructed over B, G, R color space. Skin and Nonskin dataset is generated using skin textures from face images of…
15 runs1 likes10 downloads11 reach7 impact
245057 instances - 4 features - 2 classes - 0 missing values
* Dataset Title: Volcanoes on Venus - JARtool experiment Data Set Experiment: D1 * Source: Michael C. Burl MS 126-347, JPL 4800 Oak Grove Drive Pasadena, CA 91109 (818) 393-5345 Michael.C.Burl '@'…
125 runs0 likes4 downloads4 reach7 impact
8753 instances - 4 features - 5 classes - 0 missing values
__Major changes w.r.t. version 2: ignored variable 3 in this upload as this seems to be ea perfect predictor.__ Tamilnadu Electricity Board Hourly Readings dataset. Real-time readings were collected…
0 runs0 likes2 downloads2 reach5 impact
45781 instances - 4 features - 20 classes - 0 missing values
* Dataset Title: Volcanoes on Venus - JARtool experiment Data Set Experiment: B6 * Source: Michael C. Burl MS 126-347, JPL 4800 Oak Grove Drive Pasadena, CA 91109 (818) 393-5345 Michael.C.Burl '@'…
111 runs0 likes2 downloads2 reach7 impact
10130 instances - 4 features - 5 classes - 0 missing values
* Dataset Title: Volcanoes on Venus - JARtool experiment Data Set Experiment: C1 * Source: Michael C. Burl MS 126-347, JPL 4800 Oak Grove Drive Pasadena, CA 91109 (818) 393-5345 Michael.C.Burl '@'…
54 runs0 likes3 downloads3 reach7 impact
28626 instances - 4 features - 5 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…
739 runs0 likes7 downloads7 reach8 impact
475 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…
768 runs0 likes7 downloads7 reach8 impact
450 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…
751 runs0 likes7 downloads7 reach8 impact
475 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…
703 runs0 likes6 downloads6 reach7 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…
1073 runs0 likes10 downloads10 reach7 impact
140 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…
775 runs0 likes12 downloads12 reach8 impact
2178 instances - 4 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…
41 runs0 likes2 downloads2 reach7 impact
27 instances - 4 features - 4 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…
1030 runs0 likes8 downloads8 reach7 impact
132 instances - 4 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…
694 runs0 likes7 downloads7 reach7 impact
83 instances - 4 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…
1116 runs0 likes9 downloads9 reach7 impact
120 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…
111 runs0 likes5 downloads5 reach7 impact
52 instances - 4 features - 2 classes - 0 missing values
87 persons with lupus nephritis. Followed up 15+ years. 35 deaths. Var = duration of disease. Over 40 baseline variables avaiable from authors. Description : For description of this data set arising…
737 runs0 likes8 downloads8 reach7 impact
87 instances - 4 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 reach7 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…
802 runs0 likes8 downloads8 reach8 impact
662 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…
792 runs0 likes7 downloads7 reach8 impact
662 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 likes6 downloads6 reach8 impact
185 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…
1088 runs0 likes8 downloads8 reach7 impact
132 instances - 4 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…
746 runs0 likes7 downloads7 reach7 impact
72 instances - 4 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…
708 runs0 likes5 downloads5 reach8 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…
813 runs0 likes7 downloads7 reach8 impact
662 instances - 4 features - 2 classes - 0 missing values
1. Title: Haberman's Survival Data 2. Sources: (a) Donor: Tjen-Sien Lim (limt@stat.wisc.edu) (b) Date: March 4, 1999 3. Past Usage: 1. Haberman, S. J. (1976). Generalized Residuals for Log-Linear…
3241 runs1 likes19 downloads20 reach2 impact
306 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…
771 runs0 likes9 downloads9 reach8 impact
468 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…
1190 runs0 likes9 downloads9 reach7 impact
111 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…
739 runs0 likes6 downloads6 reach8 impact
662 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…
1268 runs0 likes11 downloads11 reach7 impact
131 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…
1202 runs0 likes9 downloads9 reach7 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…
572 runs0 likes6 downloads6 reach7 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…
119 runs0 likes5 downloads5 reach7 impact
39 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…
514 runs0 likes7 downloads7 reach7 impact
130 instances - 4 features - 2 classes - 0 missing values
One of the data sets used in the book "Analyzing Categorical Data" by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. Further details concerning the book, including information on statistical…
2 runs0 likes0 downloads0 reach5 impact
108 instances - 5 features - 0 classes - 0 missing values
This S dump contains 22 data sets from the book Visualizing Data published by Hobart Press (books@hobart.com). The dump was created by data.dump() and can be read back into S by data.restore(). The…
2 runs0 likes1 downloads1 reach5 impact
8641 instances - 5 features - 0 classes - 0 missing values
This S dump contains 22 data sets from the book Visualizing Data published by Hobart Press (books@hobart.com). The dump was created by data.dump() and can be read back into S by data.restore(). The…
0 runs0 likes1 downloads1 reach7 impact
323 instances - 5 features - 0 classes - 0 missing values
DATA-SETS FROM DIGGLE, P.J. (1990). TIME SERIES : A BIOSTATISTICAL INTRODUCTION. Oxford University Press. Table: Table A1 Lutenizing hormone Information about the dataset CLASSTYPE: numeric…
0 runs0 likes0 downloads0 reach5 impact
48 instances - 5 features - 0 classes - 0 missing values
This file contains data from Regression Analysis By Example, 2nd Edition, by Samprit Chatterjee and Bertram Price, John Wiley, 1991. Data sets have names of the form 'rabe.xxx' where xxx is the page…
0 runs0 likes0 downloads0 reach5 impact
46 instances - 5 features - 0 classes - 0 missing values
This file contains data from Regression Analysis By Example, 2nd Edition, by Samprit Chatterjee and Bertram Price, John Wiley, 1991. Data sets have names of the form 'rabe.xxx' where xxx is the page…
0 runs0 likes0 downloads0 reach5 impact
70 instances - 5 features - 0 classes - 0 missing values
1. Title: Employee Selection (Ordinal ESL) 2. Source Informaion: Donor: Arie Ben David MIS, Dept. of Technology Management Holon Academic Inst. of Technology 52 Golomb St. Holon 58102 Israel…
0 runs0 likes0 downloads0 reach5 impact
488 instances - 5 features - 0 classes - 0 missing values
1. Title: Employee Selection (Ordinal ESL) 2. Source Informaion: Donor: Arie Ben David MIS, Dept. of Technology Management Holon Academic Inst. of Technology 52 Golomb St. Holon 58102 Israel…
0 runs0 likes0 downloads0 reach5 impact
488 instances - 5 features - 0 classes - 0 missing values
1. Title: Lecturers Evaluation (Ordinal LEV) 2. Source Informaion: Donor: Arie Ben David MIS, Dept. of Technology Management Holon Academic Inst. of Technology 52 Golomb St. Holon 58102 Israel…
0 runs1 likes2 downloads3 reach5 impact
1000 instances - 5 features - 0 classes - 0 missing values
1. Title: Employee Rejection\Acceptance (Orinal ERA) 2. Source Informaion: Donor: Arie Ben David MIS, Dept. of Technology Management Holon Academic Inst. of Technology 52 Golomb St. Holon 58102 Israel…
0 runs0 likes1 downloads1 reach5 impact
1000 instances - 5 features - 0 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…
0 runs0 likes1 downloads1 reach5 impact
39 instances - 5 features - 0 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…
0 runs0 likes1 downloads1 reach5 impact
150 instances - 5 features - 0 classes - 0 missing values
Information about the dataset CLASSTYPE: numeric CLASSINDEX: last
2 runs0 likes1 downloads1 reach5 impact
559 instances - 5 features - 0 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…
0 runs0 likes0 downloads0 reach5 impact
48 instances - 5 features - 0 classes - 0 missing values
Information about the dataset CLASSTYPE: numeric CLASSINDEX: last
2 runs0 likes0 downloads0 reach5 impact
559 instances - 5 features - 0 classes - 0 missing values
Information about the dataset CLASSTYPE: numeric CLASSINDEX: last
2 runs0 likes1 downloads1 reach5 impact
559 instances - 5 features - 0 classes - 0 missing values
Information about the dataset CLASSTYPE: numeric CLASSINDEX: last
2 runs0 likes1 downloads1 reach5 impact
559 instances - 5 features - 0 classes - 0 missing values
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! Identifier attribute deleted. !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! NAME: Sexual activity and the lifespan of male fruitflies TYPE: Designed (almost factorial)…
4 runs0 likes2 downloads2 reach1 impact
125 instances - 5 features - 0 classes - 0 missing values
Dataset from Smoothing Methods in Statistics (ftp stat.cmu.edu/datasets) Simonoff, J.S. (1996). Smoothing Methods in Statistics. New York: Springer-Verlag. Gasoline comnsumption is being treated as…
2 runs0 likes0 downloads0 reach1 impact
27 instances - 5 features - 0 classes - 0 missing values
Dataset from Smoothing Methods in Statistics (ftp stat.cmu.edu/datasets) Simonoff, J.S. (1996). Smoothing Methods in Statistics. New York: Springer-Verlag. Points scored per minute is being treated as…
2 runs0 likes0 downloads0 reach1 impact
96 instances - 5 features - 0 classes - 0 missing values
Data originating from the book "Analyzing Categorical Data" by Jeffrey S. Simonoff.
1085 runs0 likes9 downloads9 reach7 impact
50 instances - 5 features - 2 classes - 0 missing values
MyExampleIris
32 runs0 likes1 downloads1 reach11 impact
150 instances - 5 features - 3 classes - 0 missing values
* Dataset Title: Wall-Following Robot Navigation Data Data Set (version with 4 Attributes) * Abstract: The data were collected as the SCITOS G5 robot navigates through the room following the wall in a…
138 runs1 likes6 downloads7 reach7 impact
5456 instances - 5 features - 4 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…
0 runs0 likes2 downloads2 reach4 impact
366 instances - 5 features - classes - 2 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach1 impact
150 instances - 5 features - classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach1 impact
150 instances - 5 features - 3 classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach1 impact
150 instances - 5 features - classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach1 impact
150 instances - 5 features - 3 classes - 0 missing values
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach1 impact
14 instances - 5 features - 2 classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach1 impact
150 instances - 5 features - classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach1 impact
150 instances - 5 features - 3 classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach1 impact
150 instances - 5 features - classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach1 impact
150 instances - 5 features - 3 classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach1 impact
150 instances - 5 features - classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach1 impact
150 instances - 5 features - 3 classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach1 impact
150 instances - 5 features - classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach1 impact
150 instances - 5 features - 3 classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach1 impact
150 instances - 5 features - classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach1 impact
150 instances - 5 features - 3 classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach1 impact
150 instances - 5 features - classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach1 impact
150 instances - 5 features - 3 classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach1 impact
150 instances - 5 features - classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach1 impact
150 instances - 5 features - 3 classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach1 impact
150 instances - 5 features - classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach1 impact
150 instances - 5 features - 3 classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach1 impact
150 instances - 5 features - classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach1 impact
150 instances - 5 features - 3 classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach1 impact
150 instances - 5 features - classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach1 impact
150 instances - 5 features - 3 classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach2 impact
150 instances - 5 features - classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes1 downloads1 reach2 impact
150 instances - 5 features - 3 classes - 0 missing values
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes1 downloads1 reach1 impact
14 instances - 5 features - 2 classes - 0 missing values
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach1 impact
14 instances - 5 features - 2 classes - 0 missing values
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach1 impact
14 instances - 5 features - 2 classes - 0 missing values
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach1 impact
14 instances - 5 features - 2 classes - 0 missing values
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach1 impact
14 instances - 5 features - 2 classes - 0 missing values
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach1 impact
14 instances - 5 features - 2 classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach1 impact
150 instances - 5 features - classes - 0 missing values