Wheat Kernels
Donated on 8/2/2020
Measurements of morphological descriptors of wheat kernels from Punjab State. A machine Learning based technique was used to extract 15 features, all are real valued attributes
Dataset Characteristics
Multivariate
Subject Area
Computer Science
Associated Tasks
Classification
Feature Type
Real
# Instances
314
# Features
15
Dataset Information
Additional Information
The examined group comprised kernels of wheat : PBW-550U randomly selected for the experiment. High Quality Manual Visualisation of the external Kernel. It is non-destructive technique.The images were recorded using Basler Sca-17fc industrial graded color camera. The dataset can be used for tasks of classification.
Has Missing Values?
No
Variable Information
Area, Major Axis Length, Minor Axis Length, Perimeter, Length, Width, Thinness Ratio, Aspect Ratio, Rectangular Aspect ratio, Area Ratio, Distance Max,Distance Min, Distance Ratio, Std Deviation,Mean
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pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset wheat_kernels = fetch_ucirepo(id=596) # data (as pandas dataframes) X = wheat_kernels.data.features y = wheat_kernels.data.targets # metadata print(wheat_kernels.metadata) # variable information print(wheat_kernels.variables)
Wheat Kernels. (2020). UCI Machine Learning Repository. https://doi.org/10.24432/C5NG8N.
@misc{misc_wheat_kernels_596,
title = {{Wheat Kernels}},
year = {2020},
howpublished = {UCI Machine Learning Repository},
note = {{DOI}: https://doi.org/10.24432/C5NG8N}
}DOI
Notes
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.