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13 Data Sets

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1. Codon usage: DNA codon usage frequencies of a large sample of diverse biological organisms from different taxa

2. Forest type mapping: Multi-temporal remote sensing data of a forested area in Japan. The goal is to map different forest types using spectral data.

3. Heart Disease: 4 databases: Cleveland, Hungary, Switzerland, and the VA Long Beach

4. Thyroid Disease: 10 separate databases from Garavan Institute

5. Cervical Cancer Behavior Risk: The dataset contains 19 attributes regarding ca cervix behavior risk with class label is ca_cervix with 1 and 0 as values which means the respondent with and without ca cervix, respectively.

6. Autistic Spectrum Disorder Screening Data for Children : Children screening data for autism suitable for classification and predictive tasks

7. Autistic Spectrum Disorder Screening Data for Adolescent : Autistic Spectrum Disorder Screening Data for Adolescent. This dataset is related to classification and predictive tasks.

8. Thoracic Surgery Data: The data is dedicated to classification problem related to the post-operative life expectancy in the lung cancer patients: class 1 - death within one year after surgery, class 2 - survival.

9. Diabetic Retinopathy Debrecen Data Set: This dataset contains features extracted from the Messidor image set to predict whether an image contains signs of diabetic retinopathy or not.

10. ILPD (Indian Liver Patient Dataset): This data set contains 10 variables that are age, gender, total Bilirubin, direct Bilirubin, total proteins, albumin, A/G ratio, SGPT, SGOT and Alkphos.

11. Quadruped Mammals: The file animals.c is a data generator of structured instances representing quadruped animals

12. One-hundred plant species leaves data set: Sixteen samples of leaf each of one-hundred plant species. For each sample, a shape descriptor, fine scale margin and texture histogram are given.

13. Fertility: 100 volunteers provide a semen sample analyzed according to the WHO 2010 criteria. Sperm concentration are related to socio-demographic data, environmental factors, health status, and life habits

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