Commit 1eee1208 authored by ashivani's avatar ashivani

update readme

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The dataset consists of measurements of fetal heart rate (FHR) and uterine contraction (UC) features on cardiotocograms classified by expert obstetricians.
These `fetal cardiotocograms (CTGs)` were automatically processed and the respective diagnostic features measured. The `CTGs` were also classified by three expert obstetricians and a consensus classification label assigned to each of them. The dataset consists of `24` attributes out of which first `23` attributes describes details of `CTGs` features and last attribute called `NSP` is used to classify these `CTGs` in `normal`, `suspect` and `pathologic` on the basis of fetal state.<br/>
These `fetal cardiotocograms (CTGs)` were automatically processed and the respective diagnostic features measured. The `CTGs` were also classified by three expert obstetricians and a consensus classification label assigned to each of them. The dataset consists of `24` attributes out of which first `23` attributes describes details of `CTGs` features and last attribute called `NSP` is used to classify these `CTGs` in `1` for `normal`, `2` for`suspect` and `3` for `pathologic` on the basis of fetal state.<br/>
To know about given attributes click [here](https://gitlab.aicrowd.com/aicrowd/practice-challenges/aicrowd_CRDIO_challenge/blob/master/dataset_info.md).
......@@ -19,9 +19,9 @@ To know about given attributes click [here](https://gitlab.aicrowd.com/aicrowd/p
Following files are available in the `resources` section:
- `train.csv` - (`1700` samples) File that should be used for training and validation purposes by the user.
- `train.csv` - (`1700` samples) This csv contains the features from the cardiotocograph along with the risk state of the featus as `[1-3]` denoting `normal` ,`suspect` and `pathologic` respectively.
- `test.csv` - (`426` samples) File that will be used for actual evaluation for the leaderboard score.
- `test.csv` - (`426` samples) This csv contains the features from the cardiotocograph but not the risk state of the featus.
# 🚀 Submission
- Prepare a csv containing header as `NSP` and predicted value as digit `[1-3]` with name as `submission.csv`.
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# 🖊 Evaluation Criteria
During evaluation [F1 score](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.f1_score.html) will be used to test the efficiency of the model where,
During evaluation [F1 score](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.f1_score.html) and [accuracy](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.accuracy_score.html) will be used to test the efficiency of the model where,
<img src="https://latex.codecogs.com/gif.latex?F1%20%3D%202%20*%20%5Cfrac%7Bprecision*recall%7D%7Bprecision&plus;recall%7D"/>
**The score of only 60% of the test data will be revealed during the competition**.
# 🔗 Links
* 💪 Challenge Page: https://www.aicrowd.com/challenges/crdio
* 🗣️ Discussion Forum: https://www.aicrowd.com/challenges/crdio/discussion
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