## **Meta-Album Fungi Dataset (Mini)** Meta-Album Fungi dataset is created by sampling the Danish Fungi 2020 dataset(https://arxiv.org/abs/2103.10107), itself a sampling of the Atlas of Danish Fungi…
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1000 instances - 3 features - 25 classes - 0 missing values
## **Meta-Album Insects Dataset (Mini)** The original Insects dataset is created by the National Museum of Natural History, Paris (https://www.mnhn.fr/fr). It has more than 290 000 images in different…
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4160 instances - 3 features - 104 classes - 0 missing values
Subsampling of the dataset Internet-Advertisements (40978) 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 - 0 missing values
Subsampling of the dataset Internet-Advertisements (40978) 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 - 0 missing values
Subsampling of the dataset PhishingWebsites (4534) 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 - 31 features - 2 classes - 0 missing values
Subsampling of the dataset PhishingWebsites (4534) 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 - 31 features - 2 classes - 0 missing values
Subsampling of the dataset Internet-Advertisements (40978) 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 - 0 missing values
Subsampling of the dataset Internet-Advertisements (40978) 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 - 0 missing values
Data set of around 45 language and 25 Category. Consist of articles.
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65428 instances - 3 features - classes - 0 missing values
TEST STUDENTS DATA
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100 instances - 11 features - classes - 0 missing values
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…
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80 instances - 6 features - classes - 0 missing values
I am testing to upload data
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601 instances - 7 features - classes - 0 missing values
Context Everybody nowadays is mindful of what they eat. Counting calories and reducing fat intake is the number one advice given by all dieticians and nutritionists. Therefore, we need to know what…
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335 instances - 10 features - classes - 3 missing values
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…
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23911 instances - 6 features - classes - 3 missing values
Content This is a dataset I started building for my future personal projects, as I think this kind of data is quite hard to acquire for free and in short time. I started acquiring data on March 21st,…
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193279 instances - 4 features - classes - 29954 missing values
Context I wanted to use this dataset to combine with Toronto Police Homicide reports to determine how time of day (and specifically illumination) have an impact on crime. Content The dataset currently…
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4018 instances - 3 features - classes - 0 missing values
Nursery Database was derived from a hierarchical decision model originally developed to rank applications for nursery schools.
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12960 instances - 9 features - 5 classes - 0 missing values
Subsampling of the dataset PhishingWebsites (4534) 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 - 31 features - 2 classes - 0 missing values
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
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-verylarge.html#andes) - Number of nodes: 223 - Number of arcs: 338 - Number of parameters: 1157 -…
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5000 instances - 223 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-verylarge.html#andes) - Number of nodes: 223 - Number of arcs: 338 - Number of parameters: 1157 -…
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5000 instances - 223 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-verylarge.html#andes) - Number of nodes: 223 - Number of arcs: 338 - Number of parameters: 1157 -…
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5000 instances - 223 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-verylarge.html#andes) - Number of nodes: 223 - Number of arcs: 338 - Number of parameters: 1157 -…
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5000 instances - 223 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-verylarge.html#andes) - Number of nodes: 223 - Number of arcs: 338 - Number of parameters: 1157 -…
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5000 instances - 223 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-verylarge.html#andes) - Number of nodes: 223 - Number of arcs: 338 - Number of parameters: 1157 -…
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5000 instances - 223 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-verylarge.html#andes) - Number of nodes: 223 - Number of arcs: 338 - Number of parameters: 1157 -…
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5000 instances - 223 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-verylarge.html#andes) - Number of nodes: 223 - Number of arcs: 338 - Number of parameters: 1157 -…
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5000 instances - 223 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-verylarge.html#andes) - Number of nodes: 223 - Number of arcs: 338 - Number of parameters: 1157 -…
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5000 instances - 223 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-large.html#hepar2) - Number of nodes: 76 - Number of arcs: 112 - Number of parameters: 574 - Average…
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5000 instances - 76 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-verylarge.html#andes) - Number of nodes: 223 - Number of arcs: 338 - Number of parameters: 1157 -…
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5000 instances - 223 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-large.html#hepar2) - Number of nodes: 76 - Number of arcs: 112 - Number of parameters: 574 - Average…
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5000 instances - 76 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-large.html#hepar2) - Number of nodes: 76 - Number of arcs: 112 - Number of parameters: 574 - Average…
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5000 instances - 76 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-large.html#hepar2) - Number of nodes: 76 - Number of arcs: 112 - Number of parameters: 574 - Average…
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5000 instances - 76 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-large.html#hepar2) - Number of nodes: 76 - Number of arcs: 112 - Number of parameters: 574 - Average…
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5000 instances - 76 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-large.html#hepar2) - Number of nodes: 76 - Number of arcs: 112 - Number of parameters: 574 - Average…
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5000 instances - 76 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-large.html#hepar2) - Number of nodes: 76 - Number of arcs: 112 - Number of parameters: 574 - Average…
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5000 instances - 76 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-verylarge.html#andes) - Number of nodes: 223 - Number of arcs: 338 - Number of parameters: 1157 -…
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5000 instances - 223 features - 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
DBLP-QuAD is a scholarly question answering dataset over the DBLP knowledge graph. The dataset can also be found at https://zenodo.org/record/7643971 and…
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10000 instances - 10 features - 9999 classes - 0 missing values
HotpotQA is a new dataset with 113k Wikipedia-based question-answer pairs with four key features: (1) the questions require finding and reasoning over multiple supporting documents to answer; (2) the…
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97852 instances - 7 features - classes - 0 missing values
mki
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8 instances - 2 features - classes - 0 missing values
Elegibilidade ecommerce
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269177 instances - 2 features - 2 classes - 0 missing values
Dataset showing Data from matches played RB Leipzig prior to 14.06.2020
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102 instances - 1 features - classes - 0 missing values
26InternationalstudentsinChina-Province
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12 instances - 2 features - classes - 0 missing values
24InternationalstudentsinChina-Continent
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5 instances - 3 features - classes - 0 missing values
Context The dataset comes from one of the most important parts of a mining process: a flotation plant The main goal is to use this data to predict how much impurity is in the ore concentrate. As this…
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737453 instances - 24 features - 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
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
Nursery Database was derived from a hierarchical decision model originally developed to rank applications for nursery schools.
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12960 instances - 9 features - 5 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
Car Evaluation Database was derived from a simple hierarchical decision model originally developed for the demonstration of DEX, M. Bohanec, V. Rajkovic: Expert system for decision making. Sistemica…
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1728 instances - 7 features - 4 classes - 0 missing values
### This is a dataset with dummy description
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12 instances - 4 features - 4 classes - 0 missing values
### Description mini_insect_1
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12 instances - 4 features - 4 classes - 0 missing values
## **Meta-Album Plant Village Dataset (Micro)** The Plant Village dataset(https://data.mendeley.com/datasets/tywbtsjrjv/1) contains camera photos of 17 crop leaves. The original image resolution is…
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800 instances - 3 features - 20 classes - 0 missing values
## **Meta-Album RSICB Dataset (Extended)** RSICB128 dataset (https://github.com/lehaifeng/RSI-CB) covers 45 scene categories, assembling in total 36 000 images of resolution 128x128 px. The data…
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36707 instances - 3 features - 45 classes - 0 missing values
## **Meta-Album Fungi Dataset (Extended)** Meta-Album Fungi dataset is created by sampling the Danish Fungi 2020 dataset(https://arxiv.org/abs/2103.10107), itself a sampling of the Atlas of Danish…
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15122 instances - 3 features - 25 classes - 0 missing values
## **Meta-Album RSICB Dataset (Micro)** RSICB128 dataset (https://github.com/lehaifeng/RSI-CB) covers 45 scene categories, assembling in total 36 000 images of resolution 128x128 px. The data authors…
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800 instances - 3 features - 20 classes - 0 missing values
## **Meta-Album Insects Dataset (Extended)** The original Insects dataset is created by the National Museum of Natural History, Paris (https://www.mnhn.fr/fr). It has more than 290 000 images in…
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170506 instances - 3 features - 117 classes - 0 missing values
## **Meta-Album Plant Village Dataset (Extended)** The Plant Village dataset(https://data.mendeley.com/datasets/tywbtsjrjv/1) contains camera photos of 17 crop leaves. The original image resolution is…
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54305 instances - 3 features - 38 classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-massive.html#munin) - Number of nodes: 1041 - Number of arcs: 1397 - Number of parameters: 80592 -…
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5000 instances - 1041 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-massive.html#munin) - Number of nodes: 1041 - Number of arcs: 1397 - Number of parameters: 80592 -…
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5000 instances - 1041 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-massive.html#munin) - Number of nodes: 1041 - Number of arcs: 1397 - Number of parameters: 80592 -…
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5000 instances - 1041 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-massive.html#munin) - Number of nodes: 1041 - Number of arcs: 1397 - Number of parameters: 80592 -…
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5000 instances - 1041 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-massive.html#munin) - Number of nodes: 1041 - Number of arcs: 1397 - Number of parameters: 80592 -…
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5000 instances - 1041 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-massive.html#munin) - Number of nodes: 1041 - Number of arcs: 1397 - Number of parameters: 80592 -…
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5000 instances - 1041 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-massive.html#munin) - Number of nodes: 1041 - Number of arcs: 1397 - Number of parameters: 80592 -…
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5000 instances - 1041 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-massive.html#munin) - Number of nodes: 1041 - Number of arcs: 1397 - Number of parameters: 80592 -…
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5000 instances - 1041 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-massive.html#munin) - Number of nodes: 1041 - Number of arcs: 1397 - Number of parameters: 80592 -…
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5000 instances - 1041 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-massive.html#munin) - Number of nodes: 1041 - Number of arcs: 1397 - Number of parameters: 80592 -…
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5000 instances - 1041 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-massive.html#munin) - Number of nodes: 1041 - Number of arcs: 1397 - Number of parameters: 80592 -…
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5000 instances - 1041 features - classes - 0 missing values
We introduce AfriSenti, which consists of 14 sentiment datasets of 110,000+ tweets in 14 African languages (Amharic, Algerian Arabic, Hausa, Igbo, Kinyarwanda, Moroccan Arabic, Mozambican Portuguese,…
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111720 instances - 4 features - 3 classes - 0 missing values
punch sound
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221 instances - 1 features - classes - 0 missing values
analysis of stocks
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245 instances - 15 features - classes - 0 missing values
xscdc frfgrg
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3 instances - 1 features - classes - 0 missing values
dsd efe
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601 instances - 7 features - classes - 0 missing values
Survey to know if people self-identify as Midwesterners.
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2778 instances - 28 features - 10 classes - 1737 missing values
Survey to know if people self-identify as Midwesterners.
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2494 instances - 28 features - 9 classes - 99 missing values
Context The objective of this dataset is to create a chess engine through machine learning. In this first part we will first predict the pieces to be moved depending on the position of the chessboard…
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2632753 instances - 66 features - classes - 0 missing values
Source: Charles Gaydon This data only contains 5 variables of Productcode, Warehouse, ProductCategory, Date, Order_demand I showed that it is possible, with trivial models, to lower the mean average…
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1048575 instances - 5 features - classes - 11239 missing values
Context It's always interesting to analyse what's going on in the news but there's no good data avaialable in indian context on kaggle, so I created one. Content Apart from the main content of the…
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1568 instances - 8 features - classes - 33 missing values
Context This dataset was a part of the assignment of my coursework. Content The dataset contains 90+ columns describing different aspects of all countries like GDP, Population, Electricity-consumption…
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197 instances - 80 features - classes - 0 missing values
Context The Dow Jones Industrial Average is one of the most followed stock market indexes by investors, financial professionals and the media. Content It measures the daily price movements of 30 large…
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2766 instances - 7 features - classes - 0 missing values
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…
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4028 instances - 6 features - classes - 0 missing values
Subsampling of the dataset car (40975) 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:…
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1728 instances - 7 features - 4 classes - 0 missing values
Subsampling of the dataset car (40975) 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:…
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1728 instances - 7 features - 4 classes - 0 missing values
Subsampling of the dataset car (40975) 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:…
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1728 instances - 7 features - 4 classes - 0 missing values
Subsampling of the dataset car (40975) 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:…
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1728 instances - 7 features - 4 classes - 0 missing values
Subsampling of the dataset car (40975) 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:…
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1728 instances - 7 features - 4 classes - 0 missing values
Subsampling of the dataset dna (40670) 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:…
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2000 instances - 101 features - 3 classes - 0 missing values
Subsampling of the dataset dna (40670) 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:…
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2000 instances - 101 features - 3 classes - 0 missing values
Subsampling of the dataset dna (40670) 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:…
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2000 instances - 101 features - 3 classes - 0 missing values
Subsampling of the dataset dna (40670) 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:…
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2000 instances - 101 features - 3 classes - 0 missing values
Subsampling of the dataset kr-vs-kp (3) 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:…
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2000 instances - 37 features - 2 classes - 0 missing values
Subsampling of the dataset kr-vs-kp (3) 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:…
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2000 instances - 37 features - 2 classes - 0 missing values
Subsampling of the dataset kr-vs-kp (3) 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:…
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2000 instances - 37 features - 2 classes - 0 missing values
Subsampling of the dataset kr-vs-kp (3) 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:…
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2000 instances - 37 features - 2 classes - 0 missing values
Subsampling of the dataset kr-vs-kp (3) 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:…
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2000 instances - 37 features - 2 classes - 0 missing values
Subsampling of the dataset dna (40670) 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:…
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2000 instances - 101 features - 3 classes - 0 missing values
Subsampling of the dataset Amazon_employee_access (4135) 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 - 10 features - 2 classes - 0 missing values