Measuring Classification Performance with Python and Scikit-Learn

classification performance python confusion matrix roc curve

Classification is a supervised machine learning problem in which the task is to predict the correct class labels (two or more) for a set of observations. An essential step in developing a classifier is to evaluate its performance. Only when we understand how well a model sorts observations into the … Read more

Crime Prevention in San Francisco using XGBoost and Python

Crime Prediction using XGBoost and Python, sf crime map

This tutorial predicts crime types in San Francisco (SF) and plots them on a zoomable city map. We work with a Kaggle dataset containing past crimes and distinguish between 39 crime types, including vehicle theft, assault, and drug-related activities. We then use Python and Scikit-Learn to train a classification model … Read more

Sentiment Analysis with Naive Bayes and Logistic Regression in Python

sentiment classification python tutorial bayes regression

In this article, we develop a Python classification model that analyzes Twitter comments’ sentiment. We will train different classification models using Naive Bayes and Logistic Regression. Companies are increasingly employing similar models in a business context. They help companies deal with the vast amount of text data available online and … Read more