Subsampling of the dataset PhishingWebsites (4534) 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(…
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2000 instances - 31 features - 2 classes - 0 missing values
Subsampling of the dataset PhishingWebsites (4534) 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 - 31 features - 2 classes - 0 missing values
Subsampling of the dataset sylvine (41146) 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( self,…
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2000 instances - 21 features - 2 classes - 0 missing values
Subsampling of the dataset sylvine (41146) 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( self,…
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2000 instances - 21 features - 2 classes - 0 missing values
Subsampling of the dataset sylvine (41146) 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( self,…
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2000 instances - 21 features - 2 classes - 0 missing values
Subsampling of the dataset sylvine (41146) 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( self,…
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2000 instances - 21 features - 2 classes - 0 missing values
Subsampling of the dataset Satellite (40900) 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( self,…
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2000 instances - 37 features - 2 classes - 0 missing values
Subsampling of the dataset Satellite (40900) 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( self,…
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2000 instances - 37 features - 2 classes - 0 missing values
Subsampling of the dataset Satellite (40900) 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( self,…
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2000 instances - 37 features - 2 classes - 0 missing values
Subsampling of the dataset Satellite (40900) 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( self,…
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2000 instances - 37 features - 2 classes - 0 missing values
Subsampling of the dataset Satellite (40900) 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( self,…
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2000 instances - 37 features - 2 classes - 0 missing values
Subsampling of the dataset sf-police-incidents (42732) with seed=0 args.nrows=2000 args.ncols=100 args.nclasses=10 args.no_stratify=True Generated with the following source code: ```python def…
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2000 instances - 9 features - 2 classes - 0 missing values
Subsampling of the dataset sf-police-incidents (42732) with seed=4 args.nrows=2000 args.ncols=100 args.nclasses=10 args.no_stratify=True Generated with the following source code: ```python def…
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2000 instances - 9 features - 2 classes - 0 missing values
Subsampling of the dataset porto-seguro (42742) 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 - 58 features - 2 classes - 2775 missing values
Subsampling of the dataset porto-seguro (42742) 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 - 58 features - 2 classes - 2855 missing values
Subsampling of the dataset porto-seguro (42742) 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(…
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2000 instances - 58 features - 2 classes - 2863 missing values
Subsampling of the dataset porto-seguro (42742) 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 - 58 features - 2 classes - 2837 missing values
Subsampling of the dataset porto-seguro (42742) 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(…
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2000 instances - 58 features - 2 classes - 2846 missing values
Subsampling of the dataset KDDCup09-Upselling (43072) with seed=0 args.nrows=2000 args.ncols=100 args.nclasses=10 args.no_stratify=True Generated with the following source code: ```python def…
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2000 instances - 101 features - 2 classes - 3570 missing values
Subsampling of the dataset KDDCup09-Upselling (43072) with seed=1 args.nrows=2000 args.ncols=100 args.nclasses=10 args.no_stratify=True Generated with the following source code: ```python def…
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2000 instances - 101 features - 2 classes - 7121 missing values
Subsampling of the dataset KDDCup09-Upselling (43072) with seed=2 args.nrows=2000 args.ncols=100 args.nclasses=10 args.no_stratify=True Generated with the following source code: ```python def…
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2000 instances - 101 features - 2 classes - 5914 missing values
Subsampling of the dataset KDDCup09-Upselling (43072) with seed=3 args.nrows=2000 args.ncols=100 args.nclasses=10 args.no_stratify=True Generated with the following source code: ```python def…
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2000 instances - 101 features - 2 classes - 0 missing values
Subsampling of the dataset KDDCup09-Upselling (43072) with seed=4 args.nrows=2000 args.ncols=100 args.nclasses=10 args.no_stratify=True Generated with the following source code: ```python def…
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2000 instances - 101 features - 2 classes - 9426 missing values
Subsampling of the dataset sf-police-incidents (42732) with seed=1 args.nrows=2000 args.ncols=100 args.nclasses=10 args.no_stratify=True Generated with the following source code: ```python def…
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2000 instances - 9 features - 2 classes - 0 missing values
Subsampling of the dataset sf-police-incidents (42732) with seed=2 args.nrows=2000 args.ncols=100 args.nclasses=10 args.no_stratify=True Generated with the following source code: ```python def…
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2000 instances - 9 features - 2 classes - 0 missing values
Subsampling of the dataset sf-police-incidents (42732) with seed=3 args.nrows=2000 args.ncols=100 args.nclasses=10 args.no_stratify=True Generated with the following source code: ```python def…
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2000 instances - 9 features - 2 classes - 0 missing values
At Santander our mission is to help people and businesses prosper. We are always looking for ways to help our customers understand their financial health and identify which products and services might…
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200000 instances - 201 features - 2 classes - 0 missing values
Context "Predict behavior to retain customers. You can analyze all relevant customer data and develop focused customer retention programs." [IBM Sample Data Sets] Content Each row represents a…
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7043 instances - 20 features - 2 classes - 11 missing values
======================================================================================================== Seismic bumps dataset…
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2584 instances - 19 features - 2 classes - 0 missing values
Dota 2 is a popular computer game with two teams of 5 players. At the start of the game each player chooses a unique hero with different strengths and weaknesses. Source: stephen.tridgell '@'…
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102944 instances - 117 features - 2 classes - 0 missing values
Pulsar candidates collected during the HTRU survey. Pulsars are a type of star, of considerable scientific interest. Candidates must be classified in to pulsar and non-pulsar classes to aid discovery.…
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17898 instances - 9 features - 2 classes - 0 missing values
## Source: 1. C. Okan Sakar Department of Computer Engineering, Faculty of Engineering and Natural Sciences, Bahcesehir University, 34349 Besiktas, Istanbul, Turkey 2. Yomi Kastro Inveon Information…
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12330 instances - 18 features - 2 classes - 0 missing values
This is the datasets from the Kaggle Higgs Boson Machine Learning Challenge 2014. The data was downloaded from the [CERN website](http://opendata.cern.ch/record/328), which also hosts the…
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818238 instances - 31 features - 2 classes - 0 missing values
This is the datasets from the Kaggle Higgs Boson Machine Learning Challenge 2014. The data was downloaded from the [CERN website](http://opendata.cern.ch/record/328), which also hosts the…
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818238 instances - 31 features - 2 classes - 5168486 missing values
This dataset is from the "Explainable Machine Learning Challenge": > The Explainable Machine Learning Challenge is a collaboration between Google, FICO and academics at Berkeley, Oxford, Imperial, UC…
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9871 instances - 24 features - 2 classes - 12643 missing values
This dataset is a subset of the [KDDCup 2012 track 2](https://www.kaggle.com/competitions/kddcup2012-track2/) data created by Manu Joseph and Harsh Raj for the paper > Joseph, M., & Raj, H. (2022). >…
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1000000 instances - 12 features - 2 classes - 0 missing values
Mammography is the most effective method for breast cancer screening available today. However, the low positive predictive value of breast biopsy resulting from mammogram interpretation leads to…
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961 instances - 5 features - 2 classes - 160 missing values
A Tour & Travels Company Wants To Predict Whether A Customer Will Churn Or Not Based On Indicators Given Below. Help Build Predictive Models And Save The Company's Money. Perform Fascinating EDAs. The…
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954 instances - 7 features - 2 classes - 60 missing values
## Data description There are 3 types of input features: * Objective: factual information; * Examination: results of medical examination; * Subjective: information given by the patient. Features: 1.…
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70000 instances - 12 features - 2 classes - 0 missing values
This is the datasets from the Kaggle Higgs Boson Machine Learning Challenge 2014. The data was downloaded from the [CERN website](http://opendata.cern.ch/record/328), which also hosts the…
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800000 instances - 31 features - 2 classes - 5053446 missing values
This dataset is from the "Explainable Machine Learning Challenge": > The Explainable Machine Learning Challenge is a collaboration between Google, FICO and academics at Berkeley, Oxford, Imperial, UC…
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9871 instances - 24 features - 2 classes - 0 missing values
This is a classification problem to distinguish between a signal process which produces Higgs bosons and a background process which does not. ## Information The data has been produced using Monte…
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11000000 instances - 29 features - 2 classes - 0 missing values
# Data Description This is the historical price data of the FOREX EUR/CAD from Dukascopy. One instance (row) is one candlestick of one hour. The whole dataset has the data range from 1-1-2018 to…
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43825 instances - 12 features - 2 classes - 0 missing values
# Data Description This is the historical price data of the FOREX EUR/NZD from Dukascopy. One instance (row) is one candlestick of one day. The whole dataset has the data range from 1-1-2018 to…
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1832 instances - 12 features - 2 classes - 0 missing values
# Data Description This is the historical price data of the FOREX USD/DKK from Dukascopy. One instance (row) is one candlestick of one day. The whole dataset has the data range from 1-1-2018 to…
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1832 instances - 12 features - 2 classes - 0 missing values
# Data Description This is the historical price data of the FOREX EUR/CHF from Dukascopy. One instance (row) is one candlestick of one minute. The whole dataset has the data range from 1-1-2018 to…
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375840 instances - 12 features - 2 classes - 0 missing values
# Data Description This is the historical price data of the FOREX AUD/CHF from Dukascopy. One instance (row) is one candlestick of one hour. The whole dataset has the data range from 1-1-2018 to…
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43825 instances - 12 features - 2 classes - 0 missing values
# Data Description This is the historical price data of the FOREX EUR/HKD from Dukascopy. One instance (row) is one candlestick of one minute. The whole dataset has the data range from 1-1-2018 to…
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375840 instances - 12 features - 2 classes - 0 missing values
# Data Description This is the historical price data of the FOREX CAD/JPY from Dukascopy. One instance (row) is one candlestick of one minute. The whole dataset has the data range from 1-1-2018 to…
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375840 instances - 12 features - 2 classes - 0 missing values
# Data Description This is the historical price data of the FOREX CHF/JPY from Dukascopy. One instance (row) is one candlestick of one minute. The whole dataset has the data range from 1-1-2018 to…
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375840 instances - 12 features - 2 classes - 0 missing values
# Data Description This is the historical price data of the FOREX USD/CHF from Dukascopy. One instance (row) is one candlestick of one day. The whole dataset has the data range from 1-1-2018 to…
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1835 instances - 12 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…
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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…
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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…
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14 instances - 5 features - 2 classes - 0 missing values
# Data Description This is the historical price data of the FOREX EUR/JPY from Dukascopy. One instance (row) is one candlestick of one day. The whole dataset has the data range from 1-1-2018 to…
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1832 instances - 12 features - 2 classes - 0 missing values
# Data Description This is the historical price data of the FOREX EUR/USD from Dukascopy. One instance (row) is one candlestick of one day. The whole dataset has the data range from 1-1-2018 to…
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1837 instances - 12 features - 2 classes - 0 missing values
# Data Description This is the historical price data of the FOREX AUD/CAD from Dukascopy. One instance (row) is one candlestick of one day. The whole dataset has the data range from 1-1-2018 to…
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1834 instances - 12 features - 2 classes - 0 missing values
# Data Description This is the historical price data of the FOREX EUR/CAD from Dukascopy. One instance (row) is one candlestick of one day. The whole dataset has the data range from 1-1-2018 to…
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1834 instances - 12 features - 2 classes - 0 missing values
# Data Description This is the historical price data of the FOREX USD/JPY from Dukascopy. One instance (row) is one candlestick of one minute. The whole dataset has the data range from 1-1-2018 to…
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375840 instances - 12 features - 2 classes - 0 missing values
# Data Description This is the historical price data of the FOREX AUD/JPY from Dukascopy. One instance (row) is one candlestick of one hour. The whole dataset has the data range from 1-1-2018 to…
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43825 instances - 12 features - 2 classes - 0 missing values
# Data Description This is the historical price data of the FOREX EUR/HUF from Dukascopy. One instance (row) is one candlestick of one hour. The whole dataset has the data range from 1-1-2018 to…
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43825 instances - 12 features - 2 classes - 0 missing values
# Data Description This is the historical price data of the FOREX AUD/USD from Dukascopy. One instance (row) is one candlestick of one day. The whole dataset has the data range from 1-1-2018 to…
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1834 instances - 12 features - 2 classes - 0 missing values
# Data Description This is the historical price data of the FOREX USD/CAD from Dukascopy. One instance (row) is one candlestick of one hour. The whole dataset has the data range from 1-1-2018 to…
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43825 instances - 12 features - 2 classes - 0 missing values
Binarized version of the USPS dataset (see version 2). Only instances with class labels 6 and 9 from the original dataset are considered and encoded as 0 (original class 6) and 1 (original class 9).
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1424 instances - 257 features - 2 classes - 0 missing values
Binarized version of the isolet dataset (see version 1). Only instances with class labels 1 and 2 from the original dataset are considered.
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600 instances - 618 features - 2 classes - 0 missing values
Binarized version of the cnae-9 dataset (see version 1). Only instances with class labels 1 and 2 from the original dataset are considered.
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240 instances - 857 features - 2 classes - 0 missing values
Binarized version of the semeion dataset (see version 1). Only instances with class labels 1 and 2 from the original dataset are considered.
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319 instances - 257 features - 2 classes - 0 missing values
This is a meta-dataset which describes the SVM hyperparameter tuning problem. The target attribute indicates whether tuning is required or default hyperparameter values are enough to each dataset…
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156 instances - 81 features - 2 classes - 0 missing values
This is a meta-dataset which describes the SVM hyperparameter tuning problem. The target attribute indicates whether tuning is required or default hyperparameter values are enough to each dataset…
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156 instances - 91 features - 2 classes - 0 missing values
This is a meta-dataset which describes the SVM hyperparameter tuning problem. The target attribute indicates whether tuning is required or default hyperparameter values are enough to each dataset…
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156 instances - 81 features - 2 classes - 0 missing values
The ILPD liver dataset from the OpenCC18 with the gender binary encoded so all features are numeric
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583 instances - 11 features - 2 classes - 0 missing values
Sick dataset from the opencc18 with all textual binary variables label encoded.
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3772 instances - 30 features - 2 classes - 0 missing values
Elegibilidade ecommerce
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269177 instances - 2 features - 2 classes - 0 missing values
#StudentPerfromance
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1000 instances - 8 features - 2 classes - 0 missing values
This data was extracted from the 1994 Census bureau database by Ronny Kohavi and Barry Becker (Data Mining and Visualization, Silicon Graphics). A set of reasonably clean records was extracted using…
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1000000 instances - 15 features - 2 classes - 0 missing values
Amazon Employee Access (Kaggle Competition). The data consists of real historical data collected from 2010 & 2011. Employees are manually allowed or denied access to resources over time. You must…
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32769 instances - 10 features - 2 classes - 0 missing values
Modified version of subsampled dataset from Tencent Inc. on OpenML. Duplicate rows are dropped. Columns with a high ratio of unique values are dropped. Some columns are cast to factor.
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39926 instances - 9 features - 2 classes - 0 missing values
The "Diabetes 130-Hospitals" dataset represents 10 years of clinical care at 130 U.S. hospitals and delivery networks, collected from 1999 to 2008. Each record represents the hospital admission record…
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101766 instances - 22 features - 2 classes - 0 missing values
Mushroom records drawn from The Audubon Society Field Guide to North American Mushrooms (1981). G. H. Lincoff (Pres.), New York: Alfred A. Knopf
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8124 instances - 23 features - 2 classes - 0 missing values
This data contains general demographic information on internet users in 1997.
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10108 instances - 71 features - 2 classes - 2699 missing values
Communities and Crime (Binarized) The following changes were introduced to OpenML Dataset 315. * binarized 'racepctblack' at 0.06 binarized 'ViolentCrimesPerPop' at 0.2
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1994 instances - 129 features - 2 classes - 39202 missing values
National Longitudinal Survey (Binarized) Survey results from the U.S. Bureau of Labor Statistics to gather information on the labour market activities and other life events of several groups. The…
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4908 instances - 17 features - 2 classes - 0 missing values
IBM Employee Attrition Data The dataset used in the code pattern is supplied by Kaggle and contains HR analytics data of employees that stay and leave. The types of data include metrics such as…
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1470 instances - 35 features - 2 classes - 0 missing values
IBM Employee Attrition Data The dataset used in the code pattern is supplied by Kaggle and contains HR analytics data of employees that stay and leave. The types of data include metrics such as…
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1470 instances - 34 features - 2 classes - 0 missing values
Predict whether income exceeds $50K/yr based on census data. Also known as Census Income dataset. Train and test sets combined. Null values represented with question mark is replaced with na. 52…
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48790 instances - 15 features - 2 classes - 6456 missing values
Law School Admissions (Binarized) Survey among students attending law school in the U.S. in 1991. The dataset was obtained from the R-package fairml. The response variable has been changed to a binary…
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20800 instances - 12 features - 2 classes - 0 missing values
Law School Admissions (Binarized) Survey among students attending law school in the U.S. in 1991. The dataset was obtained from the R-package fairml. The response variable has been changed to a binary…
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20800 instances - 11 features - 2 classes - 0 missing values
IBM Employee Attrition Data The dataset used in the code pattern is supplied by Kaggle and contains HR analytics data of employees that stay and leave. The types of data include metrics such as…
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1470 instances - 33 features - 2 classes - 0 missing values
IBM Employee Attrition Data The dataset used in the code pattern is supplied by Kaggle and contains HR analytics data of employees that stay and leave. The types of data include metrics such as…
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1470 instances - 35 features - 2 classes - 0 missing values
IBM Employee Attrition Data The dataset used in the code pattern is supplied by Kaggle and contains HR analytics data of employees that stay and leave. The types of data include metrics such as…
0 runs0 likes0 downloads0 reach0 impact
1470 instances - 34 features - 2 classes - 0 missing values
IBM Employee Attrition Data The dataset used in the code pattern is supplied by Kaggle and contains HR analytics data of employees that stay and leave. The types of data include metrics such as…
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1470 instances - 35 features - 2 classes - 0 missing values
A certain premium club boasts a large customer membership. The members pay an annual membership fee in return for using the exclusive facilities offered by this club. The fees are customized for every…
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10362 instances - 15 features - 2 classes - 12224 missing values
A certain premium club boasts a large customer membership. The members pay an annual membership fee in return for using the exclusive facilities offered by this club. The fees are customized for every…
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10362 instances - 15 features - 2 classes - 12224 missing values
This dataset includes 15856 records of individuals who are or were subscribers to this newspaper. Datasets contain demographic information like HH Income which stands for the household income, home…
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15855 instances - 19 features - 2 classes - 1430 missing values
The SATO data set used is real life data collected from a major wireless telecom operator in South Asia.
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2000 instances - 14 features - 2 classes - 453 missing values
No description available
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3333 instances - 21 features - 2 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 - 2 classes - 0 missing values
Subsampling of the dataset jannis (44131) 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( self,…
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2000 instances - 55 features - 2 classes - 0 missing values
Subsampling of the dataset jannis (44131) 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( self,…
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2000 instances - 55 features - 2 classes - 0 missing values
Subsampling of the dataset jannis (44131) 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( self,…
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2000 instances - 55 features - 2 classes - 0 missing values