bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#child) - Number of nodes: 20 - Number of arcs: 25 - Number of parameters: 230 - Average…
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5000 instances - 20 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#child) - Number of nodes: 20 - Number of arcs: 25 - Number of parameters: 230 - Average…
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5000 instances - 20 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#child) - Number of nodes: 20 - Number of arcs: 25 - Number of parameters: 230 - Average…
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5000 instances - 20 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#child) - Number of nodes: 20 - Number of arcs: 25 - Number of parameters: 230 - Average…
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5000 instances - 20 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#child) - Number of nodes: 20 - Number of arcs: 25 - Number of parameters: 230 - Average…
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5000 instances - 20 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#child) - Number of nodes: 20 - Number of arcs: 25 - Number of parameters: 230 - Average…
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5000 instances - 20 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#child) - Number of nodes: 20 - Number of arcs: 25 - Number of parameters: 230 - Average…
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5000 instances - 20 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#child) - Number of nodes: 20 - Number of arcs: 25 - Number of parameters: 230 - Average…
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5000 instances - 20 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#child) - Number of nodes: 20 - Number of arcs: 25 - Number of parameters: 230 - Average…
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5000 instances - 20 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#child) - Number of nodes: 20 - Number of arcs: 25 - Number of parameters: 230 - Average…
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5000 instances - 20 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 48 - Number of arcs: 84 - Number of parameters: 114005 -…
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5000 instances - 48 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 48 - Number of arcs: 84 - Number of parameters: 114005 -…
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5000 instances - 48 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 48 - Number of arcs: 84 - Number of parameters: 114005 -…
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5000 instances - 48 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 48 - Number of arcs: 84 - Number of parameters: 114005 -…
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5000 instances - 48 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 48 - Number of arcs: 84 - Number of parameters: 114005 -…
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5000 instances - 48 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 48 - Number of arcs: 84 - Number of parameters: 114005 -…
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5000 instances - 48 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 48 - Number of arcs: 84 - Number of parameters: 114005 -…
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5000 instances - 48 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 48 - Number of arcs: 84 - Number of parameters: 114005 -…
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5000 instances - 48 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 48 - Number of arcs: 84 - Number of parameters: 114005 -…
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5000 instances - 48 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 48 - Number of arcs: 84 - Number of parameters: 114005 -…
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5000 instances - 48 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 48 - Number of arcs: 84 - Number of parameters: 114005 -…
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5000 instances - 48 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 37 - Number of arcs: 46 - Number of parameters: 509 - Average…
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5000 instances - 37 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 37 - Number of arcs: 46 - Number of parameters: 509 - Average…
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5000 instances - 37 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 37 - Number of arcs: 46 - Number of parameters: 509 - Average…
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5000 instances - 37 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 37 - Number of arcs: 46 - Number of parameters: 509 - Average…
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5000 instances - 37 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 37 - Number of arcs: 46 - Number of parameters: 509 - Average…
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5000 instances - 37 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 37 - Number of arcs: 46 - Number of parameters: 509 - Average…
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5000 instances - 37 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 37 - Number of arcs: 46 - Number of parameters: 509 - Average…
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5000 instances - 37 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 37 - Number of arcs: 46 - Number of parameters: 509 - Average…
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5000 instances - 37 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 37 - Number of arcs: 46 - Number of parameters: 509 - Average…
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5000 instances - 37 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 37 - Number of arcs: 46 - Number of parameters: 509 - Average…
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5000 instances - 37 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 37 - Number of arcs: 46 - Number of parameters: 509 - Average…
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5000 instances - 37 features - classes - 0 missing values
Context A collection of tweets (in dutch) and features, gathered in april 2022 using the Twitter API. A small portion of the tweets are annotated by volunteer annotators. The main task is to identify…
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451200 instances - 20 features - 0 classes - 0 missing values
This motor third-part liability (MTPL) pricing dataset describes 1 Mio insurance policies and their corresponding claim counts, see Mayer, M., Meier, D. and Wuthrich, M.V. (2023) SHAP for Actuaries:…
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1000000 instances - 7 features - 0 classes - 0 missing values
A copy of PLK_Mini dataset from Meta album Set0
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3440 instances - 3 features - 86 classes - 3440 missing values
daily bike dataset
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731 instances - 13 features - 606 classes - 0 missing values
daily bike dataset
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731 instances - 13 features - 606 classes - 0 missing values
No data.
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83 instances - 2309 features - 4 classes - 0 missing values
No data.
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187 instances - 19994 features - 2 classes - 0 missing values
No data.
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102 instances - 12601 features - 2 classes - 0 missing values
No data.
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253 instances - 15155 features - 2 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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96 instances - 4027 features - 11 classes - 19667 missing values
No data.
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96 instances - 4027 features - 9 classes - 19667 missing values
No data.
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66 instances - 4027 features - 3 classes - 12269 missing values
No data.
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203 instances - 12601 features - 5 classes - 0 missing values
No data.
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72 instances - 7130 features - 4 classes - 0 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 - 7130 features - 2 classes - 0 missing values
No data.
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85 instances - 22284 features - 2 classes - 0 missing values
No data.
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77 instances - 5470 features - 2 classes - 0 missing values
No data.
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62 instances - 2001 features - 2 classes - 0 missing values
No data.
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60 instances - 7130 features - 2 classes - 0 missing values
No data.
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97 instances - 24482 features - 2 classes - 0 missing values
No data.
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174 instances - 12534 features - 11 classes - 0 missing values
No data.
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60 instances - 5727 features - 9 classes - 0 missing values
The original MNIST image dataset of handwritten digits is a popular benchmark for image-based machine learning methods but researchers have renewed efforts to update it and develop drop-in…
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34627 instances - 785 features - 0 classes - 0 missing values
TALLO - a global tree allometry and crown architecture database. This is the Tallo dataset described in Jucker et al. (2022) but recreated with Python scripts from Laurens Bliek. The scripts can be…
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307014 instances - 21 features - 0 classes - 0 missing values
This data set consists of three types of entities: (a) the specification of an auto in terms of various characteristics, (b) its assigned insurance risk rating, (c) its normalized losses in use as…
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1000000 instances - 26 features - 0 classes - 0 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…
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111762 instances - 33 features - 0 classes - 0 missing values
Nomao collects data about places (name, phone, localization...) from many sources. Deduplication consists in detecting what data refer to the same place. Instances in the dataset compare 2 spots.The…
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34465 instances - 119 features - 0 classes - 0 missing values
The QSAR biodegradation dataset was built in the Milano Chemometrics and QSAR Research Group. The research leading to these results has received funding from the European Communitys Seventh Framework…
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1055 instances - 41 features - 2 classes - 0 missing values
A dataset relating characteristics of telephony account features and usage and whether or not the customer churned. Originally used in Discovering Knowledge in Data: An Introduction to Data…
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5000 instances - 21 features - 0 classes - 0 missing values
This dataset is for classification tasks, and has both continuous and categorical variables.
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5032 instances - 46 features - 0 classes - 0 missing values
An international e-commerce company based wants to discover key insights from their customer database. They want to use some of the most advanced machine learning techniques to study their customers.…
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10999 instances - 10 features - 0 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…
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7608 instances - 24 features - 0 classes - 0 missing values
Airlines Dataset Inspired in the regression dataset from Elena Ikonomovska. The task is to predict whether a given flight will be delayed, given the information of the scheduled departure.
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539383 instances - 8 features - 0 classes - 0 missing values
Many people struggle to get loans due to insufficient or non-existent credit histories. And, unfortunately, this population is often taken advantage of by untrustworthy lenders.Home Credit strives to…
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244280 instances - 70 features - 0 classes - 0 missing values
One of the biggest challenges of an auto dealership purchasing a used car at an auto auction is the risk of that the vehicle might have serious issues that prevent it from being sold to customers. The…
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67212 instances - 31 features - 0 classes - 0 missing values
The dataset represents 10 years (1999-2008) of clinical care at 130 US hospitals and integrated delivery networks. It includes over 50 features representing patient and hospital outcomes. Information…
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101766 instances - 48 features - 3 classes - 192849 missing values
Prediction task is to determine whether a person makes over 50K a year. Extraction was done by Barry Becker from the 1994 Census database. A set of reasonably clean records was extracted using the…
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48842 instances - 15 features - 2 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…
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26677 instances - 14 features - 3 classes - 0 missing values
This dataset is for classification tasks, and has both continuous and categorical variables.
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100959 instances - 30 features - 0 classes - 0 missing values
The data is related with direct marketing campaigns of a Portuguese banking institution. The marketing campaigns were based on phone calls. Often, more than one contact to the same client was…
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45211 instances - 17 features - 0 classes - 0 missing values
This dataset is for classification tasks, and has both continuous and categorical variables.
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23548 instances - 11 features - 0 classes - 0 missing values
This file concerns credit card applications. All attribute names and values have been changed to meaningless symbols to protect the confidentiality of the data.This dataset is interesting because…
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653 instances - 16 features - 2 classes - 0 missing values
This data set contains details of a bank's customers and the target variable is a binary variable reflecting the fact whether the customer left the bank (closed his account) or he continues to be a…
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10000 instances - 11 features - 0 classes - 0 missing values
This dataset contain attributes of dresses and their recommendations according to their sales. Sales are monitor on the basis of alternate days.The attributes present analyzed are: Recommendation,…
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500 instances - 13 features - 0 classes - 0 missing values
The dataset consists of feature vectors belonging to 12,330 sessions.The dataset was formed so that each sessionwould belong to a different user in a 1-year period to avoidany tendency to a specific…
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12330 instances - 18 features - 2 classes - 0 missing values
Thyroid disease records supplied by the Garavan Institute and J. Ross Quinlan, New South Wales Institute, Syndney, Australia. 1987.
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3103 instances - 23 features - 2 classes - 0 missing values
This dataset classifies people described by a set of attributes as good or bad credit risks.This dataset comes with a cost matrix:Good Bad (predicted) Good 0 1 (actual)Bad 5 0 It is worse to class a…
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1000 instances - 21 features - 2 classes - 0 missing values
This is a "supervised learning" challenge in machine learning. We are making available 30 datasets, all pre-formatted in given feature representations (this means that each example consists of a fixed…
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2984 instances - 145 features - 0 classes - 0 missing values
This dataset is a subset of the 1987 National Indonesia Contraceptive Prevalence Survey. The samples are married women who were either not pregnant or do not know if they were at the time of…
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1473 instances - 10 features - 0 classes - 0 missing values
This dataset is a subset of the 1987 National Indonesia Contraceptive Prevalence Survey. The samples are married women who were either not pregnant or do not know if they were at the time of…
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1473 instances - 10 features - 0 classes - 0 missing values
This dataset is a subset of the 1987 National Indonesia Contraceptive Prevalence Survey. The samples are married women who were either not pregnant or do not know if they were at the time of…
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1473 instances - 10 features - 0 classes - 0 missing values
This dataset is a subset of the 1987 National Indonesia Contraceptive Prevalence Survey. The samples are married women who were either not pregnant or do not know if they were at the time of…
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1473 instances - 10 features - 0 classes - 0 missing values
This dataset is a subset of the 1987 National Indonesia Contraceptive Prevalence Survey. The samples are married women who were either not pregnant or do not know if they were at the time of…
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1473 instances - 10 features - 0 classes - 0 missing values
test
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48842 instances - 15 features - 2 classes - 6465 missing values
Amazon Reviews data (data source) The repository has several datasets. For this case study, we are using the Electronics dataset.
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10000 instances - 3 features - classes - 0 missing values
A copy of MD_MIX_Mini dataset from Meta album Set0
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28240 instances - 69 features - 706 classes - 665053 missing values
Dataset used in the tabular data benchmark https://github.com/LeoGrin/tabular-benchmark, transformed in the same way. This dataset belongs to the "regression on both numerical and categorical…
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163065 instances - 4 features - 0 classes - 0 missing values
Dataset used in the tabular data benchmark https://github.com/LeoGrin/tabular-benchmark, transformed in the same way. This dataset belongs to the "regression on both numerical and categorical…
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1000000 instances - 6 features - 0 classes - 0 missing values
Dataset used in the tabular data benchmark https://github.com/LeoGrin/tabular-benchmark, transformed in the same way. This dataset belongs to the "regression on both numerical and categorical…
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188318 instances - 125 features - 0 classes - 0 missing values
Dataset used in the tabular data benchmark https://github.com/LeoGrin/tabular-benchmark, transformed in the same way. This dataset belongs to the "regression on both numerical and categorical…
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5465575 instances - 12 features - 0 classes - 0 missing values
Dataset used in the tabular data benchmark https://github.com/LeoGrin/tabular-benchmark, transformed in the same way. This dataset belongs to the "regression on both numerical and categorical…
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55319 instances - 736 features - 0 classes - 0 missing values
Dataset used in the tabular data benchmark https://github.com/LeoGrin/tabular-benchmark, transformed in the same way. This dataset belongs to the "regression on both numerical and categorical…
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52031 instances - 5 features - 0 classes - 0 missing values
Dataset used in the tabular data benchmark https://github.com/LeoGrin/tabular-benchmark, transformed in the same way. This dataset belongs to the "regression on both numerical and categorical…
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4177 instances - 9 features - 0 classes - 0 missing values
Dataset used in the tabular data benchmark https://github.com/LeoGrin/tabular-benchmark, transformed in the same way. This dataset belongs to the "regression on both numerical and categorical…
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8885 instances - 256 features - 0 classes - 0 missing values
This synthetic dataset contains demographic and clinical data used to train a classifier to predict a diagnosis (of schizophrenia or depression) and assess the model performance for intersectional…
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11000 instances - 20 features - 0 classes - 0 missing values
Dataset used in the tabular data benchmark https://github.com/LeoGrin/tabular-benchmark, transformed in the same way. This dataset belongs to the "classification on both numerical and categorical…
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4966 instances - 12 features - 2 classes - 0 missing values