```
import pandas as pd 

# Load the dataset 
dataset = pd.read_csv('dataset.csv')

# Separate the data into input and output fields 
X = dataset.iloc[:, :-1].values
y = dataset.iloc[:, -1].values

# Split the dataset into training and test sets 
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0)

# Calculate the parameters of the model 
from sklearn.linear_model import LogisticRegression
classifier = LogisticRegression()
classifier.fit(X_train, y_train)

# Predict the test set 
y_pred = classifier.predict(X_test)

# Evaluate the results 
from sklearn.metrics import accuracy_score
score = accuracy_score(y_test, y_pred)
print("The accuracy score is: " + str(score))
```
Crea un programma in Python per classificare un dato set di dati