Classifier Precision, Explained

An image that shows a classifier classifying examples with positive and negative predictions, and then an accompanying equation that visualizes classification precision as true positives divided by true positives plus false positives.

This blog post explains precision in classifiers and machine learning models. It will explain what precision is, the pros and cons of this metric, how to improve precision, and more. Table of Contents: A Quick Review of Classification Precision Basics Pros and Cons of Precision How to Improve Precision Alternatives to Precision If there’s something … Read more

Sklearn confusion_matrix, Explained

An image of a confusion matrix, similar to the type of confusion matrix that we would make with Sklearn confusion_matrix.

Scikit-learn, which is affectionately known as sklearn among Python data scientists, is a Python library that offers a wide range of machine learning tools. Among these tools is the confusion_matrix function, which is indispensable when working on classification problems. So in this tutorial, I’ll show you how to use the sklearn confusion_matrix function. I’ll give … Read more

Classification Accuracy, Explained

An image of an arrow hitting a bullseye, and the equation for classification accuracy.

This blog post will explain classification accuracy. It will explain what accuracy is, the pros and cons of this metric, how to improve accuracy, and more. Table of Contents: A Quick Review of Classification Classification Accuracy Basics Pros and Cons of Accuracy How to Improve Accuracy Alternatives to Accuracy If you need something specific, you … Read more

False Negative: What they are, Why They’re Bad, and 7 Ways to Fix Them

An image that shows False Negatives, and how they're related to classification threshold, TP, TN, and FP.

When you’re working with classification and detection systems, you’ll commonly hear the term “False Negative.” You might be asking, what is a False Negative? And if you’re a serious machine learning practitioner, how do you fix them? Well, if you’re asking yourself these questions, you’re in luck. In this tutorial, I’m going to explain all … Read more

The 5 Python Skills You Need Before You Study Machine Learning

And image showing the 5 Python skills you need before you study machine learning.

Machine learning is a very powerful skill. And machine learning is a valuable skill. According to Glassdoor, the average salary for a machine learning engineer is about $140,000 in 2023. Mastering machine learning could increase your earning power a lot. The question is, how? What’s the best way to get started with machine learning? What … Read more

False Positive, Explained

An image of False Positives, that also shows the relation of FPs to TPs, FNs, TNs, and classification threshold.

Have you ever had someone talk about a classification system or medical diagnostics and mention a “False Positive?” It’s ok … False positives can be confusing if you haven’t worked with classifiers and detection systems before. But they’re important … Which is why, in this blog post, I’m going to explain almost everything you need … Read more

True Negative, Explained

An image that shows True Negatives in the context of the classification threshold, True Positives, False Positives, and False Negatives.

If you want to master building classification systems for machine learning, you need to understand how to evaluate classifiers. And in turn, that means you need to understand classification metrics. In classification there are a wide variety of metrics, like precision, recall, sensitivity, accuracy, and many others, but most of these metrics are actually based … Read more

The Best Way to Plot an ROC Curve in Python

An image that shows an ROC curve in Python, made with the Seaborn Objects API.

This tutorial will show you how to plot an ROC curve in Python using the Seaborn Objects visualization package. The tutorial is divided into sections for easy navigation, so if you need anything specific, just click on the appropriate link below. Table of Contents: Quick Review of ROC Curves Setup Create Data Plot the ROC … Read more

True Positive, Explained

An image that shows True Positives among other classified examples that include TN, FP, and FN.

When you begin immersing yourself in the world of classification systems, you’ll encounter a large number of different classification metrics: precision; recall; accuracy; sensitivity and specificity; F1-score; and many more. But as you begin digging into these metrics you’ll find another quantity that underpins them all: true positives. To understand classification generally as well as … Read more