Datasets:
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age
int8 40
95
| has_anaemia
bool 2
classes | creatinine_phosphokinase_concentration_in_blood
float64 23
7.86k
| has_diabetes
bool 2
classes | heart_ejection_fraction
float64 14
80
| has_high_blood_pressure
bool 2
classes | platelets_concentration_in_blood
float64 25.1k
850k
| serum_creatinine_concentration_in_blood
float64 0.5
9.4
| serum_sodium_concentration_in_blood
float64 113
148
| is_male
bool 2
classes | is_smoker
bool 2
classes | days_in_study
int64 4
285
| is_dead
class label 2
classes |
---|---|---|---|---|---|---|---|---|---|---|---|---|
75 | false | 582 | false | 20 | true | 265,000 | 1.9 | 130 | true | false | 4 | 1yes
|
55 | false | 7,861 | false | 38 | false | 263,358.03 | 1.1 | 136 | true | false | 6 | 1yes
|
65 | false | 146 | false | 20 | false | 162,000 | 1.3 | 129 | true | true | 7 | 1yes
|
50 | true | 111 | false | 20 | false | 210,000 | 1.9 | 137 | true | false | 7 | 1yes
|
65 | true | 160 | true | 20 | false | 327,000 | 2.7 | 116 | false | false | 8 | 1yes
|
90 | true | 47 | false | 40 | true | 204,000 | 2.1 | 132 | true | true | 8 | 1yes
|
75 | true | 246 | false | 15 | false | 127,000 | 1.2 | 137 | true | false | 10 | 1yes
|
60 | true | 315 | true | 60 | false | 454,000 | 1.1 | 131 | true | true | 10 | 1yes
|
65 | false | 157 | false | 65 | false | 263,358.03 | 1.5 | 138 | false | false | 10 | 1yes
|
80 | true | 123 | false | 35 | true | 388,000 | 9.4 | 133 | true | true | 10 | 1yes
|
75 | true | 81 | false | 38 | true | 368,000 | 4 | 131 | true | true | 10 | 1yes
|
62 | false | 231 | false | 25 | true | 253,000 | 0.9 | 140 | true | true | 10 | 1yes
|
45 | true | 981 | false | 30 | false | 136,000 | 1.1 | 137 | true | false | 11 | 1yes
|
50 | true | 168 | false | 38 | true | 276,000 | 1.1 | 137 | true | false | 11 | 1yes
|
49 | true | 80 | false | 30 | true | 427,000 | 1 | 138 | false | false | 12 | 0no
|
82 | true | 379 | false | 50 | false | 47,000 | 1.3 | 136 | true | false | 13 | 1yes
|
87 | true | 149 | false | 38 | false | 262,000 | 0.9 | 140 | true | false | 14 | 1yes
|
45 | false | 582 | false | 14 | false | 166,000 | 0.8 | 127 | true | false | 14 | 1yes
|
70 | true | 125 | false | 25 | true | 237,000 | 1 | 140 | false | false | 15 | 1yes
|
48 | true | 582 | true | 55 | false | 87,000 | 1.9 | 121 | false | false | 15 | 1yes
|
65 | true | 52 | false | 25 | true | 276,000 | 1.3 | 137 | false | false | 16 | 0no
|
65 | true | 128 | true | 30 | true | 297,000 | 1.6 | 136 | false | false | 20 | 1yes
|
68 | true | 220 | false | 35 | true | 289,000 | 0.9 | 140 | true | true | 20 | 1yes
|
53 | false | 63 | true | 60 | false | 368,000 | 0.8 | 135 | true | false | 22 | 0no
|
75 | false | 582 | true | 30 | true | 263,358.03 | 1.83 | 134 | false | false | 23 | 1yes
|
80 | false | 148 | true | 38 | false | 149,000 | 1.9 | 144 | true | true | 23 | 1yes
|
95 | true | 112 | false | 40 | true | 196,000 | 1 | 138 | false | false | 24 | 1yes
|
70 | false | 122 | true | 45 | true | 284,000 | 1.3 | 136 | true | true | 26 | 1yes
|
58 | true | 60 | false | 38 | false | 153,000 | 5.8 | 134 | true | false | 26 | 1yes
|
82 | false | 70 | true | 30 | false | 200,000 | 1.2 | 132 | true | true | 26 | 1yes
|
94 | false | 582 | true | 38 | true | 263,358.03 | 1.83 | 134 | true | false | 27 | 1yes
|
85 | false | 23 | false | 45 | false | 360,000 | 3 | 132 | true | false | 28 | 1yes
|
50 | true | 249 | true | 35 | true | 319,000 | 1 | 128 | false | false | 28 | 1yes
|
50 | true | 159 | true | 30 | false | 302,000 | 1.2 | 138 | false | false | 29 | 0no
|
65 | false | 94 | true | 50 | true | 188,000 | 1 | 140 | true | false | 29 | 1yes
|
69 | false | 582 | true | 35 | false | 228,000 | 3.5 | 134 | true | false | 30 | 1yes
|
90 | true | 60 | true | 50 | false | 226,000 | 1 | 134 | true | false | 30 | 1yes
|
82 | true | 855 | true | 50 | true | 321,000 | 1 | 145 | false | false | 30 | 1yes
|
60 | false | 2,656 | true | 30 | false | 305,000 | 2.3 | 137 | true | false | 30 | 0no
|
60 | false | 235 | true | 38 | false | 329,000 | 3 | 142 | false | false | 30 | 1yes
|
70 | false | 582 | false | 20 | true | 263,358.03 | 1.83 | 134 | true | true | 31 | 1yes
|
50 | false | 124 | true | 30 | true | 153,000 | 1.2 | 136 | false | true | 32 | 1yes
|
70 | false | 571 | true | 45 | true | 185,000 | 1.2 | 139 | true | true | 33 | 1yes
|
72 | false | 127 | true | 50 | true | 218,000 | 1 | 134 | true | false | 33 | 0no
|
60 | true | 588 | true | 60 | false | 194,000 | 1.1 | 142 | false | false | 33 | 1yes
|
50 | false | 582 | true | 38 | false | 310,000 | 1.9 | 135 | true | true | 35 | 1yes
|
51 | false | 1,380 | false | 25 | true | 271,000 | 0.9 | 130 | true | false | 38 | 1yes
|
60 | false | 582 | true | 38 | true | 451,000 | 0.6 | 138 | true | true | 40 | 1yes
|
80 | true | 553 | false | 20 | true | 140,000 | 4.4 | 133 | true | false | 41 | 1yes
|
57 | true | 129 | false | 30 | false | 395,000 | 1 | 140 | false | false | 42 | 1yes
|
68 | true | 577 | false | 25 | true | 166,000 | 1 | 138 | true | false | 43 | 1yes
|
53 | true | 91 | false | 20 | true | 418,000 | 1.4 | 139 | false | false | 43 | 1yes
|
60 | false | 3,964 | true | 62 | false | 263,358.03 | 6.8 | 146 | false | false | 43 | 1yes
|
70 | true | 69 | true | 50 | true | 351,000 | 1 | 134 | false | false | 44 | 1yes
|
60 | true | 260 | true | 38 | false | 255,000 | 2.2 | 132 | false | true | 45 | 1yes
|
95 | true | 371 | false | 30 | false | 461,000 | 2 | 132 | true | false | 50 | 1yes
|
70 | true | 75 | false | 35 | false | 223,000 | 2.7 | 138 | true | true | 54 | 0no
|
60 | true | 607 | false | 40 | false | 216,000 | 0.6 | 138 | true | true | 54 | 0no
|
49 | false | 789 | false | 20 | true | 319,000 | 1.1 | 136 | true | true | 55 | 1yes
|
72 | false | 364 | true | 20 | true | 254,000 | 1.3 | 136 | true | true | 59 | 1yes
|
45 | false | 7,702 | true | 25 | true | 390,000 | 1 | 139 | true | false | 60 | 1yes
|
50 | false | 318 | false | 40 | true | 216,000 | 2.3 | 131 | false | false | 60 | 1yes
|
55 | false | 109 | false | 35 | false | 254,000 | 1.1 | 139 | true | true | 60 | 0no
|
45 | false | 582 | false | 35 | false | 385,000 | 1 | 145 | true | false | 61 | 1yes
|
45 | false | 582 | false | 80 | false | 263,358.03 | 1.18 | 137 | false | false | 63 | 0no
|
60 | false | 68 | false | 20 | false | 119,000 | 2.9 | 127 | true | true | 64 | 1yes
|
42 | true | 250 | true | 15 | false | 213,000 | 1.3 | 136 | false | false | 65 | 1yes
|
72 | true | 110 | false | 25 | false | 274,000 | 1 | 140 | true | true | 65 | 1yes
|
70 | false | 161 | false | 25 | false | 244,000 | 1.2 | 142 | false | false | 66 | 1yes
|
65 | false | 113 | true | 25 | false | 497,000 | 1.83 | 135 | true | false | 67 | 1yes
|
41 | false | 148 | false | 40 | false | 374,000 | 0.8 | 140 | true | true | 68 | 0no
|
58 | false | 582 | true | 35 | false | 122,000 | 0.9 | 139 | true | true | 71 | 0no
|
85 | false | 5,882 | false | 35 | false | 243,000 | 1 | 132 | true | true | 72 | 1yes
|
65 | false | 224 | true | 50 | false | 149,000 | 1.3 | 137 | true | true | 72 | 0no
|
69 | false | 582 | false | 20 | false | 266,000 | 1.2 | 134 | true | true | 73 | 1yes
|
60 | true | 47 | false | 20 | false | 204,000 | 0.7 | 139 | true | true | 73 | 1yes
|
70 | false | 92 | false | 60 | true | 317,000 | 0.8 | 140 | false | true | 74 | 0no
|
42 | false | 102 | true | 40 | false | 237,000 | 1.2 | 140 | true | false | 74 | 0no
|
75 | true | 203 | true | 38 | true | 283,000 | 0.6 | 131 | true | true | 74 | 0no
|
55 | false | 336 | false | 45 | true | 324,000 | 0.9 | 140 | false | false | 74 | 0no
|
70 | false | 69 | false | 40 | false | 293,000 | 1.7 | 136 | false | false | 75 | 0no
|
67 | false | 582 | false | 50 | false | 263,358.03 | 1.18 | 137 | true | true | 76 | 0no
|
60 | true | 76 | true | 25 | false | 196,000 | 2.5 | 132 | false | false | 77 | 1yes
|
79 | true | 55 | false | 50 | true | 172,000 | 1.8 | 133 | true | false | 78 | 0no
|
59 | true | 280 | true | 25 | true | 302,000 | 1 | 141 | false | false | 78 | 1yes
|
51 | false | 78 | false | 50 | false | 406,000 | 0.7 | 140 | true | false | 79 | 0no
|
55 | false | 47 | false | 35 | true | 173,000 | 1.1 | 137 | true | false | 79 | 0no
|
65 | true | 68 | true | 60 | true | 304,000 | 0.8 | 140 | true | false | 79 | 0no
|
44 | false | 84 | true | 40 | true | 235,000 | 0.7 | 139 | true | false | 79 | 0no
|
57 | true | 115 | false | 25 | true | 181,000 | 1.1 | 144 | true | false | 79 | 0no
|
70 | false | 66 | true | 45 | false | 249,000 | 0.8 | 136 | true | true | 80 | 0no
|
60 | false | 897 | true | 45 | false | 297,000 | 1 | 133 | true | false | 80 | 0no
|
42 | false | 582 | false | 60 | false | 263,358.03 | 1.18 | 137 | false | false | 82 | 0no
|
60 | true | 154 | false | 25 | false | 210,000 | 1.7 | 135 | true | false | 82 | 1yes
|
58 | false | 144 | true | 38 | true | 327,000 | 0.7 | 142 | false | false | 83 | 0no
|
58 | true | 133 | false | 60 | true | 219,000 | 1 | 141 | true | false | 83 | 0no
|
63 | true | 514 | true | 25 | true | 254,000 | 1.3 | 134 | true | false | 83 | 0no
|
70 | true | 59 | false | 60 | false | 255,000 | 1.1 | 136 | false | false | 85 | 0no
|
60 | true | 156 | true | 25 | true | 318,000 | 1.2 | 137 | false | false | 85 | 0no
|
63 | true | 61 | true | 40 | false | 221,000 | 1.1 | 140 | false | false | 86 | 0no
|
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YAML Metadata
Error:
"configs[0]" must be of type object
Heart failure
The Heart failure dataset from Kaggle. Predict patient death from earth failure given some personal medical data .
Configurations and tasks
Configuration | Task | Description |
---|---|---|
death | Binary classification | Did the patient die? |
Usage
from datasets import load_dataset
dataset = load_dataset("mstz/heart_failure", "death")["train"]
Features
Feature | Type |
---|---|
age |
int8 |
has_anaemia |
int8 |
creatinine_phosphokinase_concentration_in_blood |
float64 |
has_diabetes |
int8 |
heart_ejection_fraction |
float64 |
has_high_blood_pressure |
int8 |
platelets_concentration_in_blood |
float64 |
serum_creatinine_concentration_in_blood |
float64 |
serum_sodium_concentration_in_blood |
float64 |
sex |
int8 |
is_smoker |
int8 |
days_in_study |
int64 |
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