#modelage
28 runs0 likes0 downloads0 reach0 impact
202 instances - 13 features - 3 classes - 202 missing values
Iris DataSet
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150 instances - 5 features - 3 classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
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150 instances - 5 features - 3 classes - 0 missing values
A Gold Standard of ~4,400 questions, answers, and comments from Stack Overflow, manually annotated for polarity. The dataset has been used for developing the EMTk toolkit for polarity detection from…
0 runs0 likes0 downloads0 reach0 impact
4423 instances - 2 features - 3 classes - 0 missing values
A Gold Standard of ~4,400 questions, answers, and comments from Stack Overflow, manually annotated for polarity. The dataset has been used for developing the EMTk toolkit for polarity detection from…
0 runs0 likes0 downloads0 reach0 impact
3097 instances - 2 features - 3 classes - 0 missing values
A Gold Standard of ~4,400 questions, answers, and comments from Stack Overflow, manually annotated for polarity. The dataset has been used for developing the EMTk toolkit for polarity detection from…
0 runs0 likes0 downloads0 reach0 impact
1326 instances - 2 features - 3 classes - 0 missing values
A Gold Standard of ~4,400 questions, answers, and comments from Stack Overflow, manually annotated for polarity. The dataset has been used for developing the EMTk toolkit for polarity detection from…
0 runs0 likes0 downloads0 reach0 impact
4423 instances - 2 features - 3 classes - 0 missing values
This is perhaps the best known database to be found in the pattern recognition literature. Fisher's paper is a classic in the field and is referenced frequently to this day. (See Duda & Hart, for…
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149 instances - 5 features - 3 classes - 0 missing values
Subsampling of the dataset Diabetes130US (4541) with seed=1 args.nrows=2000 args.ncols=100 args.nclasses=10 args.no_stratify=True Generated with the following source code: ```python def subsample(…
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2000 instances - 50 features - 3 classes - 3790 missing values
Subsampling of the dataset Diabetes130US (4541) with seed=2 args.nrows=2000 args.ncols=100 args.nclasses=10 args.no_stratify=True Generated with the following source code: ```python def subsample(…
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2000 instances - 50 features - 3 classes - 3820 missing values
Subsampling of the dataset Diabetes130US (4541) with seed=3 args.nrows=2000 args.ncols=100 args.nclasses=10 args.no_stratify=True Generated with the following source code: ```python def subsample(…
0 runs0 likes0 downloads0 reach0 impact
2000 instances - 50 features - 3 classes - 3814 missing values
Subsampling of the dataset Diabetes130US (4541) with seed=0 args.nrows=2000 args.ncols=100 args.nclasses=10 args.no_stratify=True Generated with the following source code: ```python def subsample(…
0 runs0 likes0 downloads0 reach0 impact
2000 instances - 50 features - 3 classes - 3850 missing values
Subsampling of the dataset Diabetes130US (4541) with seed=4 args.nrows=2000 args.ncols=100 args.nclasses=10 args.no_stratify=True Generated with the following source code: ```python def subsample(…
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2000 instances - 50 features - 3 classes - 3764 missing values
No data.
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72 instances - 7130 features - 3 classes - 0 missing values
No data.
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72 instances - 12583 features - 3 classes - 0 missing values
No data.
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66 instances - 4027 features - 3 classes - 12269 missing values
cars1-pmlb
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392 instances - 8 features - 3 classes - 0 missing values
allbp-pmlb
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3772 instances - 30 features - 3 classes - 0 missing values
analcatdata_happiness-pmlb
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60 instances - 4 features - 3 classes - 0 missing values
new-thyroid-pmlb
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215 instances - 6 features - 3 classes - 0 missing values
A brief description of your dataset.
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3 instances - 3 features - 3 classes - 0 missing values
User profile data for San Francisco OkCupid users published in [Kim, A. Y., & Escobedo-Land, A. (2015). OKCupid data for introductory statistics and data science courses. Journal of Statistics…
0 runs0 likes0 downloads0 reach2 impact
50789 instances - 20 features - 3 classes - 154107 missing values
No data.
307 runs0 likes0 downloads0 reach0 impact
1000000 instances - 41 features - 3 classes - 0 missing values
No data.
1038 runs0 likes0 downloads0 reach0 impact
55296 instances - 10 features - 3 classes - 0 missing values
No data.
63 runs0 likes0 downloads0 reach0 impact
1000000 instances - 41 features - 3 classes - 0 missing values
No data.
965 runs0 likes0 downloads0 reach0 impact
55296 instances - 10 features - 3 classes - 0 missing values
1. Title: Contraceptive Method Choice 2. Sources: (a) Origin: This dataset is a subset of the 1987 National Indonesia Contraceptive Prevalence Survey (b) Creator: Tjen-Sien Lim (limt@stat.wisc.edu)…
24352 runs0 likes21 downloads21 reach12 impact
1473 instances - 10 features - 3 classes - 0 missing values
This database contains all legal 8-ply positions in the game of connect-4 in which neither player has won yet, and in which the next move is not forced. Attributes represent board positions on a 6x6…
9766 runs0 likes12 downloads12 reach28 impact
67557 instances - 43 features - 3 classes - 0 missing values
Originally from the StatLog project. The raw data is still available on [UCI](https://archive.ics.uci.edu/ml/datasets/Molecular+Biology+(Splice-junction+Gene+Sequences)). The data consists of 3,186…
7063 runs0 likes9 downloads9 reach26 impact
3186 instances - 181 features - 3 classes - 0 missing values
This data has been prepared to analyze factors related to readmission as well as other outcomes pertaining to patients with diabetes. The data are submitted on behalf of the Center for Clinical and…
0 runs2 likes18 downloads20 reach17 impact
101766 instances - 50 features - 3 classes - 0 missing values
### Description ### This dataset is part of a collection datasets based on the game "Jungle Chess" (a.k.a. Dou Shou Qi). For a description of the rules, please refer to the paper (link attached). The…
6905 runs0 likes6 downloads6 reach19 impact
44819 instances - 7 features - 3 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 runs1 likes12 downloads13 reach16 impact
10936 instances - 28 features - 3 classes - 0 missing values
person credit-related information
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100000 instances - 28 features - 3 classes - 62162 missing values
Data reported to the police about the circumstances of personal injury road accidents in Great Britain from 1979, and the maker and model information of vehicles involved in the respective accident.…
0 runs0 likes1 downloads1 reach1 impact
363243 instances - 67 features - 3 classes - 2181757 missing values
Data on educational transitions for a sample of 500 Irish schoolchildren aged 11 in 1967. The data were collected by Greaney and Kelleghan (1984), and reanalyzed by Raftery and Hout (1985, 1993). ###…
16174 runs0 likes0 downloads0 reach0 impact
500 instances - 6 features - 2 classes - 32 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 likes0 downloads0 reach0 impact
83 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 likes0 downloads0 reach0 impact
87 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…
119 runs0 likes0 downloads0 reach0 impact
50 instances - 6 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…
103 runs0 likes0 downloads0 reach0 impact
92 instances - 10 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…
1034 runs0 likes0 downloads0 reach0 impact
100 instances - 7 features - 2 classes - 0 missing values
Data file: This data from "Problem-Solving" on "backache in pregnancy" is in somewhat different format from that listed in the book. Each integer is preceded by a space. This makes it easier to read.…
174 runs0 likes0 downloads0 reach0 impact
180 instances - 32 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…
1105 runs0 likes0 downloads0 reach0 impact
250 instances - 3 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 likes0 downloads0 reach0 impact
97 instances - 11 features - 2 classes - 0 missing values
Schizophrenic Eye-Tracking Data in Rubin and Wu (1997) Biometrics. Yingnian Wu (wu@hustat.harvard.edu) [14/Oct/97] Information about the dataset CLASSTYPE: nominal CLASSINDEX: last
748 runs0 likes0 downloads0 reach0 impact
340 instances - 15 features - 2 classes - 834 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…
103 runs0 likes0 downloads0 reach0 impact
52 instances - 9 features - 2 classes - 0 missing values
PRO FOOTBALL SCORES (raw data appears after the description below) How well do the oddsmakers of Las Vegas predict the outcome of professional football games? Is there really a home field advantage -…
16080 runs0 likes0 downloads0 reach0 impact
672 instances - 10 features - 2 classes - 1200 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 likes0 downloads0 reach0 impact
132 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…
743 runs0 likes0 downloads0 reach0 impact
200 instances - 8 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 likes0 downloads0 reach0 impact
120 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…
886 runs0 likes0 downloads0 reach0 impact
264 instances - 5 features - 2 classes - 0 missing values
February 23, 1982 The 1982 annual meetings of the American Statistical Association (ASA) will be held August 16-19, 1982 in Cincinnati. At that meeting, the ASA Committee on Statistical Graphics plans…
759 runs0 likes0 downloads0 reach0 impact
209 instances - 9 features - 2 classes - 15 missing values
### Description Cylinder bands UCI dataset - Process delays known as cylinder banding in rotogravure printing were substantially mitigated using control rules discovered by decision tree induction.…
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540 instances - 38 features - 2 classes - 999 missing values
### Description Cylinder bands UCI dataset - Process delays known as cylinder banding in rotogravure printing were substantially mitigated using control rules discovered by decision tree induction.…
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540 instances - 38 features - 2 classes - 999 missing values
### Description Cylinder bands UCI dataset - Process delays known as cylinder banding in rotogravure printing were substantially mitigated using control rules discovered by decision tree induction.…
0 runs0 likes0 downloads0 reach0 impact
540 instances - 38 features - 2 classes - 999 missing values
Date: Tue, 15 Nov 88 15:44:08 EST From: stan To: aha@ICS.UCI.EDU 1. Title: Final settlements in labor negotitions in Canadian industry 2. Source Information -- Creators:…
7681 runs0 likes17 downloads17 reach13 impact
57 instances - 17 features - 2 classes - 326 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 likes0 downloads0 reach0 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…
707 runs0 likes0 downloads0 reach0 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…
773 runs0 likes0 downloads0 reach0 impact
950 instances - 10 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 likes0 downloads0 reach0 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…
759 runs0 likes0 downloads0 reach0 impact
250 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…
744 runs0 likes0 downloads0 reach0 impact
8192 instances - 33 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…
734 runs0 likes0 downloads0 reach0 impact
506 instances - 14 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 likes0 downloads0 reach0 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…
763 runs0 likes0 downloads0 reach0 impact
250 instances - 101 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…
709 runs0 likes0 downloads0 reach0 impact
48 instances - 5 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 likes0 downloads0 reach0 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…
745 runs0 likes0 downloads0 reach0 impact
240 instances - 125 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 likes0 downloads0 reach0 impact
159 instances - 10 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…
754 runs0 likes0 downloads0 reach0 impact
38 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…
608 runs1 likes9 downloads10 reach15 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…
764 runs0 likes0 downloads0 reach0 impact
100 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…
683 runs0 likes0 downloads0 reach0 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…
589 runs0 likes0 downloads0 reach0 impact
22784 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…
708 runs0 likes0 downloads0 reach0 impact
286 instances - 10 features - 2 classes - 9 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 likes0 downloads0 reach0 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…
1176 runs0 likes0 downloads0 reach0 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…
760 runs0 likes0 downloads0 reach0 impact
6574 instances - 15 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 reach15 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…
771 runs0 likes0 downloads0 reach0 impact
500 instances - 26 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…
135 runs0 likes0 downloads0 reach0 impact
3190 instances - 61 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…
143 runs0 likes0 downloads0 reach0 impact
531 instances - 102 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…
1032 runs0 likes0 downloads0 reach0 impact
151 instances - 6 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…
857 runs0 likes0 downloads0 reach0 impact
9961 instances - 15 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…
639 runs0 likes0 downloads0 reach0 impact
20000 instances - 17 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…
766 runs0 likes0 downloads0 reach0 impact
2000 instances - 217 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…
176 runs0 likes0 downloads0 reach0 impact
101 instances - 17 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…
131 runs0 likes0 downloads0 reach0 impact
1340 instances - 17 features - 2 classes - 20 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 likes0 downloads0 reach0 impact
406 instances - 9 features - 2 classes - 14 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…
173 runs0 likes0 downloads0 reach0 impact
106 instances - 58 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 likes0 downloads0 reach0 impact
412 instances - 9 features - 2 classes - 96 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…
772 runs0 likes0 downloads0 reach0 impact
2310 instances - 20 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…
801 runs0 likes0 downloads0 reach0 impact
841 instances - 71 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…
758 runs0 likes11 downloads11 reach15 impact
2000 instances - 77 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 likes0 downloads0 reach0 impact
52 instances - 25 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…
652 runs0 likes0 downloads0 reach0 impact
12960 instances - 9 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 likes0 downloads0 reach0 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…
722 runs0 likes0 downloads0 reach0 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…
780 runs0 likes0 downloads0 reach0 impact
178 instances - 14 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…
1139 runs0 likes0 downloads0 reach0 impact
132 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…
727 runs0 likes0 downloads0 reach0 impact
205 instances - 26 features - 2 classes - 59 missing values