Poker Hand

Donated on 12/31/2006

Purpose is to predict poker hands

Dataset Characteristics

Multivariate

Subject Area

Games

Associated Tasks

Classification

Feature Type

Categorical, Integer

# Instances

1025010

# Features

10

Dataset Information

Additional Information

Each record is an example of a hand consisting of five playing cards drawn from a standard deck of 52. Each card is described using two attributes (suit and rank), for a total of 10 predictive attributes. There is one Class attribute that describes the "Poker Hand". The order of cards is important, which is why there are 480 possible Royal Flush hands as compared to 4 (one for each suit - explained in ftp://ftp.ics.uci.edu/pub/machine-learning-databases/poker/poker-hand.names).

Has Missing Values?

No

Variables Table

Variable NameRoleTypeDescriptionUnitsMissing Values
S1FeatureIntegerno
C1FeatureIntegerno
S2FeatureIntegerno
C2FeatureIntegerno
S3FeatureIntegerno
C3FeatureIntegerno
S4FeatureIntegerno
C4FeatureIntegerno
S5FeatureIntegerno
C5FeatureIntegerno

0 to 10 of 11

Additional Variable Information

1) S1 "Suit of card #1" Ordinal (1-4) representing {Hearts, Spades, Diamonds, Clubs} 2) C1 "Rank of card #1" Numerical (1-13) representing (Ace, 2, 3, ... , Queen, King) 3) S2 "Suit of card #2" Ordinal (1-4) representing {Hearts, Spades, Diamonds, Clubs} 4) C2 "Rank of card #2" Numerical (1-13) representing (Ace, 2, 3, ... , Queen, King) 5) S3 "Suit of card #3" Ordinal (1-4) representing {Hearts, Spades, Diamonds, Clubs} 6) C3 "Rank of card #3" Numerical (1-13) representing (Ace, 2, 3, ... , Queen, King) 7) S4 "Suit of card #4" Ordinal (1-4) representing {Hearts, Spades, Diamonds, Clubs} 8) C4 "Rank of card #4" Numerical (1-13) representing (Ace, 2, 3, ... , Queen, King) 9) S5 "Suit of card #5" Ordinal (1-4) representing {Hearts, Spades, Diamonds, Clubs} 10) C5 "Rank of card 5" Numerical (1-13) representing (Ace, 2, 3, ... , Queen, King) 11) CLASS "Poker Hand" Ordinal (0-9) 0: Nothing in hand; not a recognized poker hand 1: One pair; one pair of equal ranks within five cards 2: Two pairs; two pairs of equal ranks within five cards 3: Three of a kind; three equal ranks within five cards 4: Straight; five cards, sequentially ranked with no gaps 5: Flush; five cards with the same suit 6: Full house; pair + different rank three of a kind 7: Four of a kind; four equal ranks within five cards 8: Straight flush; straight + flush 9: Royal flush; {Ace, King, Queen, Jack, Ten} + flush

Papers Citing this Dataset

Evolving Large-Scale Data Stream Analytics based on Scalable PANFIS

By Mahardhika Pratama, Choiru Za'in, Eric Pardede. 2018

Published in Knowledge-based System, 2018.

Why Linguistic Fuzzy Rule Based Classification Systems perform well in Big Data Applications?

By Alberto Fernández, Abdulrahman Altalhi, Saleh Alshomrani, Francisco Herrera. 2017

Published in Int. J. Comput. Intell. Syst..

Concept Drift Adaptation by Exploiting Historical Knowledge

By Yu Sun, Ke Tang, Zexuan Zhu, Xin Yao. 2017

Published in ArXiv.

A MapReduce Approach to Address Big Data Classification Problems Based on the Fusion of Linguistic Fuzzy Rules

By Sara Río, Victoria López, José Benítez, Francisco Herrera. 2015

Published in Int. J. Comput. Intell. Syst..

Parallel k nearest neighbor graph construction using tree-based data structures

By Nazneen Rajani, Kate McArdle, Inderjit Dhillon. 2015

Published in 1st High Performance Graph Mining workshop.

0 to 5 of 7

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7 citations
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Creators

Robert Cattral

Franz Oppacher

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