Warm Up: Machine Learning with a Heart Hosted By DrivenData
Can you predict the presence or absence of heart disease in patients given basic medical information? This is the smallest, least complex dataset on DrivenData, and a great place to dive into the world of data science competitions.
Your goal is to predict the binary class
heart_disease_present, which represents whether or not a patient has heart disease:
0represents no heart disease present
1represents heart disease present
- List of features
- Example of features
- Performance metric
- Submission Format
- Format example
There are 14 columns in the dataset, where the
patient_id column is a unique and random identifier. The remaining 13 features are described in the section below.
slope_of_peak_exercise_st_segment(type: int): the slope of the peak exercise ST segment, an electrocardiography read out indicating quality of blood flow to the heart
thal(type: categorical): results of thallium stress test measuring blood flow to the heart, with possible values
resting_blood_pressure(type: int): resting blood pressure
chest_pain_type(type: int): chest pain type (4 values)
num_major_vessels(type: int): number of major vessels (0-3) colored by flourosopy
fasting_blood_sugar_gt_120_mg_per_dl(type: binary): fasting blood sugar > 120 mg/dl
resting_ekg_results(type: int): resting electrocardiographic results (values 0,1,2)
serum_cholesterol_mg_per_dl(type: int): serum cholestoral in mg/dl
oldpeak_eq_st_depression(type: float): oldpeak = ST depression induced by exercise relative to rest, a measure of abnormality in electrocardiograms
age(type: int): age in years
max_heart_rate_achieved(type: int): maximum heart rate achieved (beats per minute)
exercise_induced_angina(type: binary): exercise-induced chest pain (
Feature data example
Here's an example of one of the rows in the dataset so that you can see the kinds of values you might expect in the dataset. Some are binary, some are integers, some are floats, and some are categorical. There are no missing values.
Performance is evaluated according to binary log loss.
The format for the submission file is two columns with the
heart_disease_present. This competition uses log loss as its evaluation metric, so the
heart_disease_present values you should submit are the probabilities that a patient has heart disease (not the binary label).
For example, if you predicted...
.csv file that you submit would look like:
patient_id,heart_disease_present olalu7,0.5 z9n6mx,0.5 5k4413,0.5 mrg7q5,0.5 uki4do,0.5 kev1sk,0.5 9n6let,0.5 jxmtyg,0.5 51s2ff,0.5 ... 5bbknr,0.5 hr6pjx,0.5 r4hsar,0.5 4cezdf,0.5 palhcc,0.5 bwoyg6,0.5 j8i7ve,0.5 t2zn1n,0.5 oxf8kj,0.5 aeiv0y,0.5
Good luck and enjoy this problem! If you have any questions you can always visit the user forum!
Warm Up: Machine Learning with a Heart: Rules and Terms of Data Use
DrivenData Competition Rules
One account per participant
You cannot sign up to DrivenData from multiple accounts and therefore you cannot submit from multiple accounts.
Private sharing of code
Privately sharing code or data outside of teams is not permitted.
Public dissemination of entries
DrivenData and the competition host have the right to publicly disseminate any entries or models.
Open licensing of winners
Winning solutions need to be made available under The MIT License (an open source software license commonly described at http://opensource.org/licenses/MIT) in order to be eligible for recognition and prize money if offered.
Documentation for winning solutions
Winning solutions must be documented using the provided Winning Model Documentation Template in order to be eligible for recognition and prize money if offered.
The number of submissions per day is restricted to a fixed value on a per-competition basis. Any attempt to circumvent this limit will result in disqualification.
External data is not allowed unless otherwise noted explicitly on these competition pages. Participants agree to make no attempt to use additional data or data sources not provided on these competition pages.
These are the complete, official rules for the Competition (the 'Competition Rules') and incorporate by reference the contents of the Competition Website listed above.
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Data use and code sharing
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