practice 1

import pandas as pd
from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import train_test_split
from sklearn.metrics import recall_score, precision_recall_fscore_support

sensitivity_score = recall_score
def specificity_score(y_true, y_pred):
    p, r, f, s = precision_recall_fscore_support(y_true, y_pred)
    return r[0]

df = pd.read_csv('https://sololearn.com/uploads/files/titanic.csv')
df['male'] = df['Sex'] == 'male'
X = df[['Pclass', 'male', 'Age', 'Siblings/Spouses', 'Parents/Children', 'Fare']].values
y = df['Survived'].values

X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=5)

model = LogisticRegression()
model.fit(X_train, y_train)
y_pred = model.predict(X_test)

print("sensitivity:", sensitivity_score(y_test, y_pred))
print("specificity:", specificity_score(y_test, y_pred))