one-hundred-plants-margin
type: Item
instance of: data set
OpenML dataset ID: 1491
dataset version identifier: 1
description: **Author**: James Cope, Thibaut Beghin, Paolo Remagnino, Sarah Barman. \N**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/One-hundred+plant+species+leaves+data+set) - 2010 \N**Please cite**: Charles Mallah, James Cope, James Orwell. Plant Leaf Classification Using Probabilistic Integration of Shape, Texture and Margin Features. Signal Processing, Pattern Recognition and Applications, in press. 2013. \N\N### Description\N\NOne-hundred plant species leaves dataset (Class = Margin).\N \N### Sources\N```\N (a) Original owners of colour Leaves Samples:\N\N James Cope, Thibaut Beghin, Paolo Remagnino, Sarah Barman. \N The colour images are not included. \N The Leaves were collected in the Royal Botanic Gardens, Kew, UK. \N email: james.cope@kingston.ac.uk \N \N (b) This dataset consists of work carried out by James Cope, Charles Mallah, and James Orwell. \N Donor of database Charles Mallah: charles.mallah@kingston.ac.uk; James Cope: james.cope@kingston.ac.uk \N```\N\N### Dataset Information\N\NThe original data directory contains the binary images (masks) of the leaf samples (colour images not included).\NThere are three features for each image: Shape, Margin and Texture.\NFor each feature, a 64 element vector is given per leaf sample.\NThese vectors are taken as a contiguous descriptor (for shape) or histograms (for texture and margin).\NSo, there are three different files, one for each feature problem: \N * 'data_Sha_64.txt' -> prediction based on shape\N * 'data_Tex_64.txt' -> prediction based on texture\N * 'data_Mar_64.txt' -> prediction based on margin [**dataset provided here**] \N\NEach row has a 64-element feature vector followed by the Class label.\NThere is a total of 1600 samples with 16 samples per leaf class (100 classes), and no missing values.\N\N### Attributes Information\N\NThree 64 element feature vectors per sample.\N\N### Relevant Papers\N\NCharles Mallah, James Cope, James Orwell. \NPlant Leaf Classification Using Probabilistic Integration o…
upload date: 2015-05-25T00:00:00Z
full work available at URL: one-hundred-plants-margin.arff
default target attribute: Class
OpenML semantic tag: Chemistry
OpenML semantic tag: Life Science
number of binary features: 0
number of classes: 100
number of features: 65
number of instances: 1600
number of instances with missing values: 0
number of missing values: 0
number of numeric features: 64
number of symbolic features: 1
file format: ARFF
MaRDI profile type: Dataset
description: OpenML dataset with id 1491