Predicting who will survive on the Titanic with logistic regression

In this recipe, we will introduce logistic regression, a basic classifier. We will apply these techniques on a Kaggle dataset where the goal is to predict survival on the Titanic based on real data (see http://www.kaggle.com/c/titanic).

Note

Kaggle (http://www.kaggle.com/competitions) hosts machine learning competitions where anyone can download a dataset, train a model, and test the predictions on the website.

How to do it...

1. We import the standard packages:

   >>> import numpy as np
       import pandas as pd
       import sklearn
       import sklearn.linear_model as lm
       import sklearn.model_selection as ms
       import matplotlib.pyplot as plt
       %matplotlib inline

2. We load the training and test datasets with pandas:

   >>> train = pd.read_csv('https://github.com/ipython-books'
                           '/cookbook-2nd-data/blob/master/'
                           'titanic_train.csv?raw=true')
       test = pd.read_csv('https:/...