Solving Logistic Regression Problems with Python

Hardik Jaroli shows how we can solve logistic regression problems using Python, using the Titanic data set as an example:

We will be working with the Titanic Data Set from Kaggle. We’ll be trying to predict a classification- survival or deceased.

Let’s begin by implementing Logistic Regression in Python for classification. We’ll use a “semi-cleaned” version of the titanic data set, if you use the data set hosted directly on Kaggle, you may need to do some additional cleaning.

Click through for the demo.

Related Posts

Calculating AUC in R

Andrew Treadway shows how you can calculate Area Under the Curve in R: AUC is an important metric in machine learning for classification. It is often used as a measure of a model’s performance. In effect, AUC is a measure between 0 and 1 of a model’s performance that rank-orders predictions from a model. For […]

Read More

Python versus R (Again)

Alex Woodie looks at whether Python is dominating R in the data science space: There is some evidence that Python’s popularity is hurting R usage. According to the TIOBE Index, Python is currently the third most popular language in the world, behind perennial heavyweights Java and C. From August 2018 to August 2019, Python usage surged […]

Read More

Categories

April 2019
MTWTFSS
« Mar May »
1234567
891011121314
15161718192021
22232425262728
2930