INNER CODE UNIT · Python
evaluate_model
bansalkanav/Ultimate-Data-Science-Toolkit---From-Python-Basics-to-GenerativeAI · Module 5 - MLOPs/4. Orchestrate ML Pipeline/my_workflow_script.py:59
def evaluate_model(model, X_train_scaled, y_train, X_test_scaled, y_test):
"""
Evaluating the model.
"""
y_train_pred = model.predict(X_train_scaled)
y_test_pred = model.predict(X_test_scaled)
train_score = metrics.accuracy_score(y_train, y_train_pred)
test_score = metrics.accuracy_score(y_test, y_test_pred)
return train_score, test_score
# Workflow
@flow(name="KNN Training Flow")
def workflow():
DATA_PATH = "data/iris.csv"
INPUTS = ['SepalLengthCm', 'SepalWidthCm', 'PetalLengthCm', 'PetalWidthCm']