Dataset from the MLRR repository: http://axon.cs.byu.edu:5000/

1. Title: Teaching Assistant Evaluation 2. Sources: (a) Collector: Wei-Yin Loh (Department of Statistics, UW-Madison) (b) Donor: Tjen-Sien Lim (limt@stat.wisc.edu) (b) Date: June 7, 1997 3. Past…

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…

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…

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…

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…

The first 5 variables are all blood tests which are thought to be sensitive to liver disorders that might arise from excessive alcohol consumption. Each line in the dataset constitutes the record of a…

The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…

The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…

The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…

The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…

The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…

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…

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…

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…

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…

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…

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…

* Title: User Knowledge Modeling Data Set * Abstract: It is the real dataset about the students' knowledge status about the subject of Electrical DC Machines. The dataset had been obtained from Ph.D.…

Data from StatLib (ftp stat.cmu.edu/datasets) These data are those collected in a cloud-seeding experiment in Tasmania between mid-1964 and January 1971. Their analysis, using regression techniques…

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…

## Guess which points belong to signal track [COMET](http://comet.kek.jp/Introduction.html) is an experiment being constructed at the J-PARC proton beam laboratory in Japan. It will search for…

And another sample. (v. 2 without OpenML metainfo)

Sample with OpenML metadata.

## Guess which points belong to signal track [COMET](http://comet.kek.jp/Introduction.html) is an experiment being constructed at the J-PARC proton beam laboratory in Japan. It will search for…

## Guess which points belong to signal track [COMET](http://comet.kek.jp/Introduction.html) is an experiment being constructed at the J-PARC proton beam laboratory in Japan. It will search for…

Sampled http://www.openml.org/d/5889

Another sample of COMET_MC

simple engine data

Payments given by healthcare manufacturing companies to medical doctors or hospitals

Content Microsoft is an American multinational technology company. It develops, manufactures, licenses, supports, and sells computer software, consumer electronics, personal computers, and related…

Context Coronaviruses are a large family of viruses which may cause illness in animals or humans. In humans, several coronaviruses are known to cause respiratory infections ranging from the common…

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 numerical features" benchmark.…

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 numerical features" benchmark.…

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 numerical features" benchmark. Original…

We choose age, delivery number, delivery time, blood pressure and heart status. We classify delivery time to Premature, Timely and Latecomer. As like the delivery time we consider blood pressure in…

Context Dataset is generated through a long and complex process. Starting from scrapping the whole URLs provided on Genius.com for Game of Thrones series. Process on scrapping and cleaning the dataset…

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 numerical features" benchmark.…

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 numerical features" benchmark. Original…

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 numerical features" benchmark. Original…

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 numerical features" benchmark. Original…

Subsampling of the dataset wilt (40983) 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, seed:…

Subsampling of the dataset wilt (40983) 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, seed:…

Subsampling of the dataset wilt (40983) 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, seed:…

Subsampling of the dataset wilt (40983) 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, seed:…

Subsampling of the dataset wilt (40983) 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, seed:…

Context As you all know that, as per the observation of economists, according to the current trend, it seems that the yellow metal is performing better as an investment option in comparison to mutual…

Context People love movies because: It takes you on a journey. Its an escape from reality. Being a vivid movie watcher I always get amazed how sites like Netflix and Hotstar always exactly suggest the…

Context People love movies because: It takes you on a journey. Its an escape from reality. Being a vivid movie watcher I always get amazed how sites like Netflix and Hotstar always exactly suggest the…

Please refer to UCI's [citation policy](https://archive.ics.uci.edu/ml/citation_policy.html). Donor: Dr Roberto Lopez robertolopez '@' intelnics.com Intelnics Creators: Thomas F. Brooks, D. Stuart…

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…

Introduction TMDB.org is a crowd-sourced movie information database used by many film-related consoles, sites and apps, such as XBMC, MythTV and Plex. Dozens of media managers, mobile apps and social…

Context The stock prices dataset of a ticker is a good start to slice and dice and good for forecasting of the stock prices. The GOOG ticker data is taken Content Dataset is comprising of the below…

Context I scraped all of the currently available Urban Dictionary pages (611) on 3/26/17 Content word - the slang term added to urban dictionary definition - the definition of said term author - the…

Apple stock price of each work day since January 1st 2021. Contains highest price, lowest price, open, close, volume and adjusted close

Context I was exploring League of Legends datasets to play around but since Riot allows limited calls to their API, I've collected the data from OP.GG. Few goals of mine were to find out the best team…

Apple stock price in the first month of 2022

Apple stock price of each work day since January 1st 2021. Contains highest price, lowest price, open, close, volume and adjusted close

Apple stock price of each trading day since January 1st 2021. Contains highest price, lowest price, open, close, volume and adjusted close

Apple stock price in the first month of 2022

Auto MPG (6 variables) dataset The data concerns city-cycle fuel consumption in miles per gallon (Mpg), to be predicted in terms of 1 multivalued discrete and 5 continuous attributes (two multivalued…

DESCRIPTIVE ABSTRACT: The data set contains the oral, written and combined test scores for 2003 New Haven Fire Department promotion exams. The Race and Position for each test taker are also given.…

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newtest3

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…

Context While brainstorming ideas for a statistics project for a course last semester, the idea of utilizing data about microbreweries came up. Unfortunately after some exploration and thought, we…

ContextWhilebrainstormingideasforastatisticsprojectforacourselastsemestertheideaofutilizingdataaboutmicrobreweriescameupUnfortunatelyaftersomeexplorationandthoughtwescrappedtheideabutIvegotthisdatatoshowforitanywayContentDatawasacquiredfromhttpswwwbeermonthclubcomandcontainsinformationaboutbreweriesavailableonthesiteasofOctober1st2019NametypeofbreweryaddresswebsiteandstateareamongthedataincludedCodeusedtoscrapeisavailableathttpsgithubcombrkurzawabrewpubscraperAcknowledgementsThankstobeermonthclubforallowingthebrewpubsectiontobescrapedInspirationThisdataaloneisnttooinspiringbutmaybeitcouldbeusedasthebasisforananalysisprojectthatlooksatinformationsuchasyelpreviewsornumberoflinkstoabreweryswebsite…

This dataset contains Apple's (AAPL) stock data for the last 10 years (from 2010 to date). I believe insights from this data can be used to build useful price forecasting algorithms to aid investment.…

Oranges vs. Grapefruit The task of separating oranges and grapefruit is fairly obvious to a human, but even with manual observation there is still a bit of error. This dataset takes the color, weight,…

Context Since as a beginner in machine learning it would be a great opportunity to try some techniques to predict the outcome of the drugs that might be accurate for the patient. Content The target…

Context Ethereum a decentralized, open-source blockchain featuring smart contract functionality was proposed in 2013 by programmer Vitalik Buterin. Development was crowdfunded in 2014, and the network…

Context - World Health Organization (WHO) Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus (2019-nCoV). Content This dataset has information on the…

Context COVID19 is spreading across the globe and this data set help in analyzing to what extent the pandemic has affected different countries. Content This data set contains the total number of COVID…

Context The goal of this dataset is to provide a tidy way to access to the transcripts of speeches given by various US politicians in the context of the 2020 US Presidential Election. Transcripts have…

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 numerical features" benchmark. Original…

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 numerical features" benchmark. Original…

Subsampling of the dataset phoneme (44127) 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,…

Subsampling of the dataset phoneme (44127) 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,…

Subsampling of the dataset phoneme (44127) 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,…

Subsampling of the dataset phoneme (44127) 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,…

Subsampling of the dataset phoneme (44127) 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,…

The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…

The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…

The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…

The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…

The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…

The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…

The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…

The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…

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…

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…

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…

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…

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…

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…

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…