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Source: Original Owner: U.S. Census Bureau http://www.census.gov/ United States Department of Commerce Donor: Terran Lane and Ronny Kohavi Data Mining and Visualization Silicon Graphics. terran '@'…
0 runs1 likes5 downloads6 reach5 impact
299285 instances - 42 features - classes - 0 missing values
This is a 10% stratified subsample of the data from the 1999 ACM KDD Cup (http://www.sigkdd.org/kddcup/index.php). Modified by TunedIT (converted to ARFF format)…
25 runs1 likes35 downloads36 reach7 impact
494020 instances - 42 features - 23 classes - 0 missing values
Datasets from ACM KDD Cup (http://www.sigkdd.org/kddcup/index.php) Data set for KDD Cup 1999 Modified by TunedIT (converted to ARFF format)…
4 runs1 likes19 downloads20 reach6 impact
4898431 instances - 42 features - 23 classes - 0 missing values
The dataset contains all the statistics for each player from 2008 to 2016.
0 runs0 likes0 downloads0 reach0 impact
183978 instances - 42 features - classes - 47301 missing values
QSAR biodegradation Data Set * Abstract: Data set containing values for 41 attributes (molecular descriptors) used to classify 1055 chemicals into 2 classes (ready and not ready biodegradable). *…
265450 runs1 likes17 downloads18 reach19 impact
1055 instances - 42 features - 2 classes - 0 missing values
This dataset contains traffic violation information from all electronic traffic violations issued in the County. Any information that can be used to uniquely identify the vehicle, the vehicle owner or…
0 runs0 likes1 downloads1 reach0 impact
1578154 instances - 43 features - 4 classes - 8006541 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…
9177 runs0 likes6 downloads6 reach16 impact
67557 instances - 43 features - 3 classes - 0 missing values
This is a corrected version of the previous data file in version 1, which contained a dataset (349 instances) incorrectly merged from the original training and test sets available on UCI (there are…
0 runs0 likes2 downloads2 reach4 impact
267 instances - 45 features - 2 classes - 0 missing values
No data.
43 runs0 likes2 downloads2 reach1 impact
1000000 instances - 45 features - 2 classes - 0 missing values
No data.
47 runs0 likes1 downloads1 reach1 impact
1000000 instances - 45 features - 2 classes - 0 missing values
)), [PMLB](https://github.com/EpistasisLab/penn-ml-benchmarks/tree/master/datasets/classification/tokyo1) This is Performance co-pilot (PCP) data for the Tokyo server at Silicon Graphics International…
35 runs0 likes1 downloads1 reach12 impact
959 instances - 45 features - 2 classes - 0 missing values
SPECTF heart data This is a merged version of the separate train and test set which are usually distributed. On OpenML this train-test split can be found as one of the possible tasks. NOTE: See the…
1103 runs0 likes12 downloads12 reach8 impact
349 instances - 45 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…
106 runs0 likes5 downloads5 reach7 impact
76 instances - 46 features - 2 classes - 22 missing values
These data are estimated correlations between daily 3 p.m. wind measurements during September and October 1997 for a network of 45 stations in the Sydney region. The first column below gives a list of…
0 runs0 likes0 downloads0 reach3 impact
45 instances - 47 features - 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…
11 runs0 likes0 downloads0 reach4 impact
5880 instances - 47 features - 3 classes - 3528 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…
11 runs0 likes0 downloads0 reach4 impact
5880 instances - 47 features - 3 classes - 3528 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…
11 runs0 likes0 downloads0 reach4 impact
4704 instances - 47 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…
10 runs0 likes0 downloads0 reach4 impact
3660 instances - 47 features - 2 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…
10 runs0 likes0 downloads0 reach4 impact
5880 instances - 47 features - 3 classes - 3528 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…
10 runs0 likes0 downloads0 reach4 impact
2352 instances - 47 features - 2 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…
12 runs0 likes0 downloads0 reach4 impact
4704 instances - 47 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…
11 runs0 likes0 downloads0 reach4 impact
4704 instances - 47 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…
12 runs0 likes0 downloads0 reach4 impact
2351 instances - 47 features - 2 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…
15 runs0 likes0 downloads0 reach4 impact
4704 instances - 47 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…
11 runs0 likes1 downloads1 reach3 impact
44819 instances - 47 features - 3 classes - 10584 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…
729 runs0 likes9 downloads9 reach7 impact
45 instances - 47 features - 2 classes - 0 missing values
No data.
52 runs0 likes3 downloads3 reach2 impact
1000000 instances - 48 features - 10 classes - 0 missing values
No data.
51 runs1 likes4 downloads5 reach2 impact
1000000 instances - 48 features - 10 classes - 0 missing values
One of a set of 6 datasets describing features of handwritten numerals (0 - 9) extracted from a collection of Dutch utility maps. Corresponding patterns in different datasets correspond to the same…
32655 runs0 likes21 downloads21 reach3 impact
2000 instances - 48 features - 10 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…
792 runs0 likes8 downloads8 reach8 impact
2000 instances - 48 features - 2 classes - 0 missing values
This is a commercial application described in Weiss & Indurkhya (1995). The data describes a telecommunication problem. No further information is available. Characteristics: (10000+5000) cases, 49…
2 runs0 likes3 downloads3 reach1 impact
15000 instances - 49 features - 0 classes - 0 missing values
__Major change w.r.t. version 1: updated data type of binary variables to factor type.__ Dataset from the Agnostic Learning vs. Prior Knowledge Challenge (http://www.agnostic.inf.ethz.ch), which…
0 runs0 likes1 downloads1 reach2 impact
4562 instances - 49 features - classes - 0 missing values
The goal of this challenge is to expose the research community to real world datasets of interest to 4Paradigm. All datasets are formatted in a uniform way, though the type of data might differ. The…
0 runs0 likes0 downloads0 reach6 impact
4147 instances - 49 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 reach8 impact
15000 instances - 49 features - 2 classes - 0 missing values
Abstract: This data has been prepared to analyze factors related to readmission as well as other outcomes pertaining to patients with diabetes. Source: The data are submitted on behalf of the Center…
0 runs2 likes13 downloads15 reach6 impact
101766 instances - 50 features - 3 classes - 0 missing values
Regroups information for about 7800 different US colleges. Including geographical information, stats about the population attending and post graduation career earnings.
0 runs0 likes0 downloads0 reach0 impact
7063 instances - 50 features - 0 classes - 125494 missing values
Oil dataset Past Usage: 1. Kubat, M., Holte, R.,
200 runs3 likes18 downloads21 reach16 impact
937 instances - 50 features - 2 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes1 downloads1 reach5 impact
1000 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach5 impact
100 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes1 downloads1 reach5 impact
1000 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach5 impact
100 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach5 impact
500 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach5 impact
250 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach5 impact
500 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes2 downloads2 reach5 impact
100 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach5 impact
250 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach5 impact
100 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach5 impact
500 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach5 impact
250 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes1 downloads1 reach5 impact
1000 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach5 impact
500 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach5 impact
100 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach5 impact
500 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes1 downloads1 reach5 impact
1000 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach5 impact
250 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach5 impact
250 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes1 downloads1 reach5 impact
1000 instances - 51 features - 0 classes - 0 missing values
This is one of 41 drug design datasets. The datasets with 1143 features are formed using Adriana.Code software (www.molecular-networks.com/software/adrianacode). The molecules and outputs are taken…
0 runs0 likes0 downloads0 reach5 impact
14 instances - 51 features - 0 classes - 0 missing values
This dataset is taken from the MiniBooNE experiment and is used to distinguish electron neutrinos (signal) from muon neutrinos (background). This dataset is ordered. It first contains all signal…
6 runs0 likes3 downloads3 reach4 impact
130064 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…
781 runs0 likes8 downloads8 reach8 impact
500 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…
636 runs0 likes8 downloads8 reach8 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…
784 runs0 likes7 downloads7 reach8 impact
500 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…
621 runs0 likes8 downloads8 reach8 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…
755 runs0 likes6 downloads6 reach8 impact
250 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…
764 runs0 likes6 downloads6 reach7 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…
614 runs0 likes9 downloads9 reach8 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…
748 runs0 likes6 downloads6 reach8 impact
250 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…
766 runs0 likes7 downloads7 reach7 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…
620 runs0 likes10 downloads10 reach8 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…
775 runs0 likes6 downloads6 reach8 impact
250 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…
801 runs0 likes8 downloads8 reach8 impact
500 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…
646 runs0 likes9 downloads9 reach8 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…
786 runs0 likes6 downloads6 reach8 impact
250 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…
788 runs0 likes7 downloads7 reach7 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…
810 runs0 likes6 downloads6 reach7 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…
807 runs0 likes7 downloads7 reach8 impact
500 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…
772 runs0 likes7 downloads7 reach8 impact
500 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…
817 runs0 likes7 downloads7 reach8 impact
250 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…
773 runs0 likes6 downloads6 reach7 impact
100 instances - 51 features - 2 classes - 0 missing values
uci
0 runs0 likes0 downloads0 reach0 impact
101766 instances - 52 features - classes - 192849 missing values
Source: James P Bridge, Sean B Holden and Lawrence C Paulson University of Cambridge Computer Laboratory William Gates Building 15 JJ Thomson Avenue Cambridge CB3 0FD UK +44 (0)1223 763500…
24444 runs1 likes20 downloads21 reach35 impact
6118 instances - 52 features - 6 classes - 0 missing values
This is one of 41 drug design datasets. The datasets with 1143 features are formed using Adriana.Code software (www.molecular-networks.com/software/adrianacode). The molecules and outputs are taken…
0 runs0 likes0 downloads0 reach5 impact
31 instances - 54 features - 0 classes - 0 missing values
Normalized version of the Forest Covertype dataset (see version 1), so that the numerical values are between 0 and 1. Contains the forest cover type for 30 x 30 meter cells obtained from US Forest…
342 runs1 likes39 downloads40 reach2 impact
581012 instances - 55 features - 7 classes - 0 missing values
This is the famous covertype dataset in its binary version, retrieved 2013-11-13 from the libSVM site (called covtype.binary there). Additional to the preprocessing done there (see LibSVM site for…
22 runs0 likes9 downloads9 reach7 impact
581012 instances - 55 features - 2 classes - 0 missing values
The goal of this challenge is to expose the research community to real world datasets of interest to 4Paradigm. All datasets are formatted in a uniform way, though the type of data might differ. The…
6 runs0 likes1 downloads1 reach7 impact
83733 instances - 55 features - 4 classes - 0 missing values
This is the original version of the famous covertype dataset in ARFF format. Predicting forest cover type from cartographic variables only (no remotely sensed data). The actual forest cover type for a…
2 runs1 likes14 downloads15 reach13 impact
581012 instances - 55 features - 7 classes - 0 missing values
Predicting forest cover type from cartographic variables only (no remotely sensed data). The actual forest cover type for a given observation (30 x 30 meter cell) was determined from US Forest Service…
216 runs0 likes11 downloads11 reach2 impact
110393 instances - 55 features - 7 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…
733 runs0 likes9 downloads9 reach9 impact
7485 instances - 56 features - 2 classes - 32427 missing values
1. Title: Lung Cancer Data 2. Source Information: - Data was published in : Hong, Z.Q. and Yang, J.Y. "Optimal Discriminant Plane for a Small Number of Samples and Design Method of Classifier on the…
1238 runs0 likes17 downloads17 reach3 impact
32 instances - 57 features - 3 classes - 5 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…
754 runs0 likes10 downloads10 reach9 impact
8844 instances - 57 features - 2 classes - 34843 missing values
No data.
219 runs0 likes4 downloads4 reach2 impact
1000000 instances - 58 features - 2 classes - 0 missing values
Automated file upload of BNG(spambase)
98 runs0 likes3 downloads3 reach2 impact
1000000 instances - 58 features - 2 classes - 0 missing values
SPAM E-mail Database The "spam" concept is diverse: advertisements for products/websites, make money fast schemes, chain letters, pornography... Our collection of spam e-mails came from our postmaster…
158864 runs3 likes82 downloads85 reach3 impact
4601 instances - 58 features - 2 classes - 0 missing values
Compilation of promoters with known transcriptional start points for E. coli genes. The task is to recognize promoters in strings that represent nucleotides (one of A, G, T, or C). A promoter is a…
138 runs1 likes9 downloads10 reach3 impact
106 instances - 59 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…
173 runs0 likes6 downloads6 reach15 impact
106 instances - 59 features - 2 classes - 0 missing values
libSVM","AAD group #Dataset from the LIBSVM data repository. Preprocessing: scaled to [-1,1]
0 runs0 likes0 downloads0 reach5 impact
3175 instances - 61 features - 0 classes - 0 missing values
This dataset summarizes a heterogeneous set of features about articles published by Mashable in a period of two years. The goal is to predict the number of shares in social networks (popularity). *…
0 runs0 likes3 downloads3 reach3 impact
39644 instances - 61 features - 0 classes - 0 missing values
The problem is to learn a regression equation/rule/tree to predict the activity from the descriptive structural attributes. The data and methodology is described in detail in: - King, Ross .D., Hurst,…
5 runs0 likes1 downloads1 reach1 impact
186 instances - 61 features - 0 classes - 0 missing values
No data.
296 runs0 likes7 downloads7 reach1 impact
1000000 instances - 61 features - 2 classes - 0 missing values
No data.
50 runs0 likes3 downloads3 reach1 impact
1000000 instances - 61 features - 2 classes - 0 missing values