Let's first show how we can use a python function to make a classification.
Before running the code, make sure you've installed the package.
python -m pip install human-learn
The fare_based
function defined below can be used to make predictions.
from hulearn.datasets import load_titanic
df = load_titanic(as_frame=True)
X, y = df.drop(columns=['survived']), df['survived']
def fare_based(dataf, threshold=10):
return np.array(dataf['fare'] > threshold).astype(int)
In the next video we'll explore how to make it into a scikit-learn compatible classifier.