Jute Pest
Donated on 11/17/2023
This dataset has 17 classes. Data are divided in three partition train, val and test. The classes are 0 : Beet Armyworm 1 : Black Hairy 2 : Cutworm 3 : Field Cricket 4 : Jute Aphid 5 : Jute Hairy 6 : Jute Red Mite 7 : Jute Semilooper 8 : Jute Stem Girdler 9 : Jute Stem Weevil 10 : Leaf Beetle 11 : Mealybug 12 : Pod Borer 13 : Scopula Emissaria 14 : Termite 15 : Termite odontotermes (Rambur) 16 : Yellow Mite
Dataset Characteristics
Image
Subject Area
Biology
Associated Tasks
Classification, Other
Feature Type
Categorical
# Instances
7235
# Features
17
Dataset Information
Has Missing Values?
No
Introductory Paper
By Md. Simul Hasan Talukder , Mohammad Raziuddin Chowdhury , Md Sakib Ullah Sourav , Abdullah Al Rakin , Shabbir Ahmed Shuvo , Rejwan Bin Sulaiman ,* , Musarrat Saberin Nipun , Muntarin Islam , Mst Rumpa Islam , Md Aminul Islam , Zubaer Haque . 2023
Published in Smart Agricultural Technology
Variable Information
Class Labels
0 : Beet Armyworm 1 : Black Hairy 2 : Cutworm 3 : Field Cricket 4 : Jute Aphid 5 : Jute Hairy 6 : Jute Red Mite 7 : Jute Semilooper 8 : Jute Stem Girdler 9 : Jute Stem Weevil 10 : Leaf Beetle 11 : Mealybug 12 : Pod Borer 13 : Scopula Emissaria 14 : Termite 15 : Termite odontotermes (Rambur) 16 : Yellow Mite
Reviews
There are no reviews for this dataset yet.
pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset jute_pest = fetch_ucirepo(id=920) # data (as pandas dataframes) X = jute_pest.data.features y = jute_pest.data.targets # metadata print(jute_pest.metadata) # variable information print(jute_pest.variables)
Islam,Muhammad Tanvirul. (2023). Jute Pest. UCI Machine Learning Repository. https://doi.org/10.24432/C5289P.
@misc{misc_jute_pest_920,
author = {Islam,Muhammad Tanvirul},
title = {{Jute Pest}},
year = {2023},
howpublished = {UCI Machine Learning Repository},
note = {{DOI}: https://doi.org/10.24432/C5289P}
}Keywords
Creators
Muhammad Tanvirul Islam
muhammad15-14364@diu.edu.bd
DOI
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.