December 2015
Beginner to intermediate
202 pages
4h
English
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Creating a predictive model using logistic regression
Logistic regression is a statistical technique used to predict a binary outcome, for example, purchase/no-purchase.
For this recipe, we are going to use the Heart dataset from An Introduction to Statistical Learning with Applications in R.
How to do it…
- First, import the Python libraries that you need:
import pandas as pd import numpy as np import matplotlib as plt import matplotlib.pyplot as plt %matplotlib inline
- Next, define a variable for the heart data file, import the data, and view the top five rows:
data_file = '/Users/robertdempsey/Dropbox/private/Python Business Intelligence Cookbook/Data/ISL/Heart.csv' heart = pd.read_csv(data_file, sep=',', header=0, index_col=0, parse_dates=True, tupleize_cols=False, ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.