diff --git a/Breast_cancer_ML/.github/workflows/cml.yaml b/Breast_cancer_ML/.github/workflows/cml.yaml new file mode 100644 index 0000000..d7497a4 --- /dev/null +++ b/Breast_cancer_ML/.github/workflows/cml.yaml @@ -0,0 +1,18 @@ +name: Breast-cancer-ML +on: [push] +jobs: + run: + runs-on: [ubuntu-latest] + container: docker://dvcorg/cml-py3:latest + steps: + - uses: actions/checkout@v2 + - name: cml_run + env: + repo_token: ${{ secrets.GITHUB_TOKEN }} + run: | + # Your ML workflow goes here + pip install -r requirements.txt + python BC_ML.py + + echo "MODEL METRICS" + diff --git a/Breast_cancer_ML/BC_ML.py b/Breast_cancer_ML/BC_ML.py index 6ce7efb..cceec16 100644 --- a/Breast_cancer_ML/BC_ML.py +++ b/Breast_cancer_ML/BC_ML.py @@ -117,6 +117,8 @@ def cross_val_pred(self): from sklearn.model_selection import cross_val_predict import scikitplot as skplt import matplotlib.pyplot as plt + from sklearn.ensemble import RandomForestClassifier + randomforest_cs = RandomForestClassifier(n_estimators=5, max_depth=5, criterion='entropy',random_state=0) pred_LogisticRegression = cross_val_predict(randomforest_cs, self.features, self.target) @@ -132,11 +134,9 @@ def visualize_performance_eval(self): - -if __name__ == '__main__': - brst_cancer_ml_model = BreastCancer() - brst_cancer_ml_model.preprocess_df() - brst_cancer_ml_model.train_ML_models() - brst_cancer_ml_model.compute_performance_evals() - brst_cancer_ml_model.visualize_performance_eval() - brst_cancer_ml_model.cross_val_pred() \ No newline at end of file +brst_cancer_ml_model = BreastCancer() +brst_cancer_ml_model.preprocess_df() +brst_cancer_ml_model.train_ML_models() +brst_cancer_ml_model.compute_performance_evals() +brst_cancer_ml_model.visualize_performance_eval() +brst_cancer_ml_model.cross_val_pred() diff --git a/Breast_cancer_ML/requirements.txt b/Breast_cancer_ML/requirements.txt new file mode 100644 index 0000000..b006044 --- /dev/null +++ b/Breast_cancer_ML/requirements.txt @@ -0,0 +1,5 @@ +numpy +pandas +matplotlib +scikit-plot +-U scikit-learn