数据挖掘常用的心脏病数据(From UCI)
2009-06-05 14:43
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http://archive.ics.uci.edu/ml/machine-learning-databases/statlog/heart/
该数据经常作为数据挖掘的示例。
This database contains 13 attributes (which have been extracted from
a larger set of 75)
Attribute Information:
------------------------
-- 1. age 年龄
-- 2. sex 性别
-- 3. chest pain type (4 values) 胸部疼痛类型
-- 4. resting blood pressure 静止血压
-- 5. serum cholestoral in mg/dl
-- 6. fasting blood sugar > 120 mg/dl
-- 7. resting electrocardiographic results (values 0,1,2)
-- 8. maximum heart rate achieved
-- 9. exercise induced angina
-- 10. oldpeak = ST depression induced by exercise relative to rest
-- 11. the slope of the peak exercise ST segment
-- 12. number of major vessels (0-3) colored by flourosopy
-- 13. thal: 3 = normal; 6 = fixed defect; 7 = reversable defect
Attributes types
-----------------
Real: 1,4,5,8,10,12
Ordered:11,
Binary: 2,6,9
Nominal:7,3,13
Variable to be predicted
------------------------
Absence (1) or presence (2) of heart disease
Cost Matrix
abse pres
absence 0 1
presence 5 0
where the rows represent the true values and the columns the predicted.
No missing values.
270 observations
该数据经常作为数据挖掘的示例。
This database contains 13 attributes (which have been extracted from
a larger set of 75)
Attribute Information:
------------------------
-- 1. age 年龄
-- 2. sex 性别
-- 3. chest pain type (4 values) 胸部疼痛类型
-- 4. resting blood pressure 静止血压
-- 5. serum cholestoral in mg/dl
-- 6. fasting blood sugar > 120 mg/dl
-- 7. resting electrocardiographic results (values 0,1,2)
-- 8. maximum heart rate achieved
-- 9. exercise induced angina
-- 10. oldpeak = ST depression induced by exercise relative to rest
-- 11. the slope of the peak exercise ST segment
-- 12. number of major vessels (0-3) colored by flourosopy
-- 13. thal: 3 = normal; 6 = fixed defect; 7 = reversable defect
Attributes types
-----------------
Real: 1,4,5,8,10,12
Ordered:11,
Binary: 2,6,9
Nominal:7,3,13
Variable to be predicted
------------------------
Absence (1) or presence (2) of heart disease
Cost Matrix
abse pres
absence 0 1
presence 5 0
where the rows represent the true values and the columns the predicted.
No missing values.
270 observations
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