View agridatasets pasture (public)

2010-11-06 09:57 by mldata | Version 1 | Rating Empty StarEmpty StarEmpty StarEmpty StarEmpty StarEmpty Star
Rating
Empty StarEmpty StarEmpty StarEmpty StarEmpty StarEmpty Star Overall (based on 0 votes)
Empty StarEmpty StarEmpty StarEmpty StarEmpty StarEmpty Star Interesting
Empty StarEmpty StarEmpty StarEmpty StarEmpty StarEmpty Star Documentation
Summary

(No information yet)

License
unknown (from Weka repository)
Dependencies
Tags
arff slurped Weka
Attribute Types
Integer,Floating Point,String
Download
# Instances: 36 / # Attributes: 23
HDF5 (21.1 KB) XML CSV ARFF LibSVM Matlab Octave
Completeness of this item currently: 44%.
You can edit this item to add more meta information and make use of the site's premium features.
Original Data Format
arff
Name
pasture-production
Version mldata
0
Comment

Pasture Production

Data source: Dave Barker AgResearch Grasslands Palmerston North New Zealand

The objective was to predict pasture production from a variety of biophysical factors. Vegetation and soil variables from areas of grazed North Island hill country with different management (fertilizer application/stocking rate) histories (1973-1994) were measured and subdivided into 36 paddocks. Ninteen vegetation (including herbage producution); soil chemical, physical and biological; and soil water variables were selected as potentially useful biophysical indicators.

Number of Instances: 36

Attribute Information: 1. fertiliser - fertiliser used - enumerated 2. slope - slope of the paddock - integer 3. aspect-dev-NW - the deviation from the north-west - integer 4. OlsenP - integer 5. MinN - integer 6. TS - integer 7. Ca-Mg - calcium magnesium ration - real 8. LOM - soil lom (g/100g) - real 9. NFIX-mean - a mean calculation - real 10. Eworms-main-3 - main 3 spp earth worms per g/m2 - real 11. Eworms-No-species - number of spp - integer 12. KUnSat - mm/hr - real 13. OM - real 14. Air-Perm - real 15. Porosity - real 16. HFRG-pct-mean - mean percent - real 17. legume-yield - kgDM/ha - real 18. OSPP-pct-mean - mean percent - real 19. Jan-Mar-mean-TDR - real 20. Annual-Mean-Runoff - in mm - real 21. root-surface-area - m2/m3 - real 22. Leaf-P - ppm - real Class: 23. pasture-prod-class - pasture production categorisation - enumerated

Class Distribution: LO - 12 MED - 12 HI - 12

Names
fertiliser,slope,aspect-dev-NW,OlsenP,MinN,TS,Ca-Mg,LOM,NFIX-mean,Eworms-main-3,
Types
  1. nominal:LL,LN,HN,HH
  2. numeric
  3. numeric
  4. numeric
  5. numeric
  6. numeric
  7. numeric
  8. numeric
  9. numeric
  10. numeric
Data (first 10 data points)
    fert... slope aspe... OlsenP MinN TS Ca-Mg LOM NFIX... Ewor... ...
    LL 25 37 8 235 235 3.64 2.11 0.061 129.9 ...
    LL 23 17 12 218 280 3.34 2.26 0.069 138.5 ...
    LL 20 18 9 243 285 3.34 1.99 0.062 109.5 ...
    LL 27 35 10 204 440 3.34 2.31 0.073 141.3 ...
    LL 8 105 8 327 455 3.64 1.3 0.067 128.0 ...
    LL 13 172 9 222 420 3.34 1.62 0.105 113.7 ...
    LL 16 68 8 303 515 3.48 3.51 0.098 92.3 ...
    LL 17 112 10 310 475 3.8 2.9 0.085 30.5 ...
    LN 20 25 9 199 410 3.2 1.77 0.02 43.3 ...
    LN 26 27 7 202 210 3.2 2.31 0.03 115.8 ...
    ... ... ... ... ... ... ... ... ... ... ...
Description

A jarfile containing 6 agricultural datasets obtained from agricultural researchers in New Zealand (agridatasets.jar, 31,200 Bytes).

URLs
(No information yet)
Publications
    Data Source
    Measurement Details
    Usage Scenario
    revision 1
    by mldata on 2010-11-06 09:57

    No one has posted any comments yet. Perhaps you would like to be the first?

    Leave a comment

    To post a comment, please sign in.

    This item was downloaded 6552 times and viewed 2835 times.

    No Tasks yet on dataset agridatasets pasture

    Submit a new Task for this Data item

    Data

    Sort by

    Disclaimer

    We are acting in good faith to make datasets submitted for the use of the scientific community available to everybody, but if you are a copyright holder and would like us to remove a dataset please inform us and we will do it as soon as possible.

    Data | Task | Method | Challenge

    Acknowledgements

    This project is supported by PASCAL (Pattern Analysis, Statistical Modelling and Computational Learning)
    PASCAL Logo
    http://www.pascal-network.org/.