Yellow cover of Model Accuracy in Python. This template resource is from 365 Data Science.

Model Accuracy in Python

Hristina Hristova

Hristina Hristova

Course Author
In this template, we classify points using the logistic regression method provided by statsmodels. Afterwards, we create a confusion matrix that makes it easier to see the correctly and incorrectly classified classes. Some other related topics you might be interested in are Logistic Regression with statsmodels in Python, Confusion Matrix with statsmodels in Python, Logistic Regression Curve in Python. The Model Accuracy in Python template is among the topics covered in detail in the 365 Data Science program.
Hristina Hristova

Hristina Hristova

Course Author


Who is it for

This is an open-access Python template that is going useful to Data Analysts, Data Scientists, Machine Learning Engineers, and anyone who is interested in learning how to solve classification problems.

How it can help you

Accuracy is one of the metrics one can use to evaluate the performance of a classification model. It is defined as the number of correctly predicted items over the number of total items in the data set. Very often, accuracy is represented as a percentage. This template can be exactly used to calculate the accuracy of a classification model.

Model Accuracy in Python

Yellow cover of Model Accuracy in Python. This template resource is from 365 Data Science.