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Egg-Producing-Chickens

Egg-Producing-Chickens

active ARFF CC0: Public Domain Visibility: public Uploaded 23-03-2022 by Stewart
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Context This data set could be used without permission for purposes of enhancing machine learning and data science. It can easily be adapted for classification, regression and clustering. At a practical level, such machine learning could be applied to determine which chickens are due for curling or approximating the number of eggs to be harvested Content GallusBreed - breed of chicken such as Buff Orpington chicken Day - an integer indicating the day on which an observation was made Age - age of the chicken in weeks GallusWeight - weight of the chicken in grams GallusEggColor - color of the eggs GallusEggWeight - weight of the eggs in grams AmountOfFeed - amount of feed in grams the chicken consumed per day EggsPerDay - number of eggs a chicken laid on a particular day GallusCombType - comb type of a particular chicken SunLightExposure - number of hours a chicken is exposed to natural light (sunlight) in a day GallusClass - chicken classes as classified by international Poultry associations GallusLegShanksColor - color of the legs/feet and shanks on them GallusBeakColor - color of the chickens beak GallusEarLobesColor - color of the chicken earlobes GallusPlumage - color of the feathers Acknowledgements http://www.chickenbreedsoftheworld.com https://www.thehappychickencoop.com/10-breeds-of-chicken-that-will-lay-lots-of-eggs-for-you https://www.starmilling.com/poultry-chicken-breeds.php https://agronomag.com/top-13-best-egg-laying-chicken-breeds Inspiration I am very passionate about Data Science, Machine Learning and Artificial Intelligence. My challenge at the moment is the lack of active participation from the African continent. It is for this reason that I am of the view that my contribution of this data set will add to the African contribution to the broader Data Science, Machine Learning and Artificial Intelligence ecosystem

16 features

GallusIDstring190 unique values
0 missing
GallusBreedstring2 unique values
0 missing
Daynumeric10 unique values
0 missing
Agenumeric167 unique values
0 missing
GallusWeightnumeric104 unique values
0 missing
GallusEggColorstring3 unique values
0 missing
GallusEggWeightnumeric183 unique values
0 missing
AmountOfFeednumeric26 unique values
0 missing
EggsPerDaynumeric2 unique values
0 missing
GallusCombTypestring2 unique values
0 missing
SunLightExposurenumeric7 unique values
0 missing
GallusClassstring1 unique values
105 missing
GallusLegShanksColorstring3 unique values
30 missing
GallusBeakColorstring2 unique values
30 missing
GallusEarLobesColorstring2 unique values
915 missing
GallusPlumagestring10 unique values
0 missing

19 properties

1000
Number of instances (rows) of the dataset.
16
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
1080
Number of missing values in the dataset.
1000
Number of instances with at least one value missing.
7
Number of numeric attributes.
0
Number of nominal attributes.
0
Percentage of nominal attributes.
Average class difference between consecutive instances.
43.75
Percentage of numeric attributes.
6.75
Percentage of missing values.
100
Percentage of instances having missing values.
0
Percentage of binary attributes.
0
Number of binary attributes.
Number of instances belonging to the least frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the most frequent class.
0.02
Number of attributes divided by the number of instances.

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