PCA-Based Anomaly Detection
Anomaly detection is a branch of machine learning that seeks to identify anomalies in datasets or data streams. Airbus uses it to predict failures in jet engines and detect anomalies […]
Principal Component Analysis
Principal Component Analysis, or PCA, is one of the minor miracles of machine learning. It’s a dimensionality-reduction technique that reduces the number of dimensions in a dataset without sacrificing a […]
Support-Vector Machines
Support-vector machines, also known as SVMs, represent the cutting edge of statistical machine learning. They are typically used for classification problems, although they can be used for regression, too. SVMs […]
Multiclass Classification
The three previous posts in this series introduced binary classification and provided working examples of its use, including sentiment analysis and spam filtering. Now it’s time to tackle multiclass classification, […]
Binary Classification: Spam Filtering
My previous post introduced a machine-learning model that used logistic regression to predict whether text input to it expresses positive or negative sentiment. We used the probability that the text […]
Binary Classification: Sentiment Analysis
One of the more novel yet practical uses for binary classification is sentiment analysis, which examines a piece of text such as a product review, a tweet, or a comment […]
Binary Classification
The machine-learning model featured in my previous post was a regression model that predicted taxi fares based on distance traveled, the day of the week, and the time of day. […]
Regression Modeling
When you build a machine-learning model, the first and most important decision you make is what learning algorithm to use to fit the model to the training data. In my […]
Regression Algorithms
Supervised-learning models come in two varieties: regression models and classification models. Regression models predict numeric outcomes, such as the price of a car. Classification models predict classes, such as the […]