Data
Early-Stage-Diabetes-Risk-Prediction-Dataset

Early-Stage-Diabetes-Risk-Prediction-Dataset

active ARFF Database: Open Database, Contents: Database Contents Visibility: public Uploaded 24-03-2022 by Dustin Carrion
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Data Set Information: This has been collected using direct questionnaires from the patients of Sylhet Diabetes Hospital in Sylhet, Bangladesh and approved by a doctor. Data Set Information: This has been col- lected using direct questionnaires from the patients of Sylhet Diabetes Hospital in Sylhet, Bangladesh and approved by a doctor. Attribute Information: Age 1.20-65 Sex 1. Male, 2.Female Polyuria 1.Yes, 2.No. Polydipsia 1.Yes, 2.No. sudden weight loss 1.Yes, 2.No. weakness 1.Yes, 2.No. Polyphagia 1.Yes, 2.No. Genital thrush 1.Yes, 2.No. visual blurring 1.Yes, 2.No. Itching 1.Yes, 2.No. Irritability 1.Yes, 2.No. delayed healing 1.Yes, 2.No. partial paresis 1.Yes, 2.No. muscle stiness 1.Yes, 2.No. Alopecia 1.Yes, 2.No. Obesity 1.Yes, 2.No. Class 1.Positive, 2.Negative. Relevant Papers: Likelihood Prediction of Diabetes at Early Stage Using Data Mining Techniques [Web Link] Authors and affiliations M. M. Faniqul IslamEmail Rahatara Ferdousi Sadikur Rahman Humayra Yasmin Bushra Citation Request: Islam, MM Faniqul, et al. 'Likelihood prediction of diabetes at early stage using data mining techniques.' Computer Vision and Machine Intelligence in Medical Image Analysis. Springer, Singapore, 2020. 113-125. Islam, MM Faniqul, et al. 'Likelihood prediction of diabetes at early stage using data mining techniques.' Computer Vision and Machine Intelligence in Medical Image Analysis. Springer, Singapore, 2020. 113-125.

17 features

Agenumeric51 unique values
0 missing
Genderstring2 unique values
0 missing
Polyuriastring2 unique values
0 missing
Polydipsiastring2 unique values
0 missing
sudden_weight_lossstring2 unique values
0 missing
weaknessstring2 unique values
0 missing
Polyphagiastring2 unique values
0 missing
Genital_thrushstring2 unique values
0 missing
visual_blurringstring2 unique values
0 missing
Itchingstring2 unique values
0 missing
Irritabilitystring2 unique values
0 missing
delayed_healingstring2 unique values
0 missing
partial_paresisstring2 unique values
0 missing
muscle_stiffnessstring2 unique values
0 missing
Alopeciastring2 unique values
0 missing
Obesitystring2 unique values
0 missing
classstring2 unique values
0 missing

19 properties

520
Number of instances (rows) of the dataset.
17
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
1
Number of numeric attributes.
0
Number of nominal attributes.
0.03
Number of attributes divided by the number of instances.
5.88
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
Average class difference between consecutive instances.
0
Percentage of missing values.

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