Course Content
Classification with Python
5. Comparing Models
Classification with Python
Challenge: Implementing Logistic Regression
Now let's implement the Logistic Regression in Python!
For this, the LogisticRegression
class is used.
![](https://codefinity-content-media.s3.eu-west-1.amazonaws.com/b71ff7ac-3932-41d2-a4d8-060e24b00129/LogisticRegressionClass.png)
Note that by default, Logistic Regression uses the ℓ2 regularization (penalty='l2'
). We will talk about regularization in later chapters. For now, we will stick to the default parameters.
The dataset for this chapter is about marketing campaigns based on phone calls from a Portuguese banking institution. The goal is to predict whether the user will subscribe to a term deposit.
The data is already preprocessed and ready to be fed to the model. Following chapters will cover the preprocessing needed for Logistic Regression.
Task
Build a Logistic Regression model and calculate the accuracy on the training set.
- Import
LogisticRegression
class. - Create an instance of class
LogisticRegression
with default parameters and train it. - Print the accuracy on the same
X, y
dataset.
Everything was clear?
Course Content
Classification with Python
5. Comparing Models
Classification with Python
Challenge: Implementing Logistic Regression
Now let's implement the Logistic Regression in Python!
For this, the LogisticRegression
class is used.
![](https://codefinity-content-media.s3.eu-west-1.amazonaws.com/b71ff7ac-3932-41d2-a4d8-060e24b00129/LogisticRegressionClass.png)
Note that by default, Logistic Regression uses the ℓ2 regularization (penalty='l2'
). We will talk about regularization in later chapters. For now, we will stick to the default parameters.
The dataset for this chapter is about marketing campaigns based on phone calls from a Portuguese banking institution. The goal is to predict whether the user will subscribe to a term deposit.
The data is already preprocessed and ready to be fed to the model. Following chapters will cover the preprocessing needed for Logistic Regression.
Task
Build a Logistic Regression model and calculate the accuracy on the training set.
- Import
LogisticRegression
class. - Create an instance of class
LogisticRegression
with default parameters and train it. - Print the accuracy on the same
X, y
dataset.
Everything was clear?