Machine Learning / Initialize Model / Classification
Updated: March 10, 2016
What is Classification?
Classification algorithms predict the class or category for a single instance of data. For example, email filters use binary classification to determine if an email is spam. There are two forms of classification tasks. The first is binary classification, where the goal is to predict one of two outcomes. The other is multiclass classification, where the goal is to predict one of many outcomes. The output of a classification algorithm is called a classifier, which can be used to predict the label of a new (unlabeled) instance.
Wondering how to select a classification algorithm? See these topics:
Machine learning algorithm cheat sheet for Azure ML
Provides a graphical decision chart to guide you through the selection process
How to choose Azure Machine Learning algorithms for clustering, classification, or regression
Explains in greater detail the different types of machine learning algorithms and how they're used
The category Initialize Classification Model includes the following modules:
Module | Description |
|---|---|
Creates a multiclass classification model using the decision forest algorithm | |
Creates a multiclass classification model using the decision jungle algorithm | |
Creates a multiclass logistic regression classification model | |
Creates a multiclass classification model using a neural network algorithm | |
Creates a multiclass classification model from an ensemble of binary classification models | |
Creates an averaged perceptron binary classification model | |
Creates a Bayes point machine binary classification model | |
Creates a binary classifier using a boosted decision tree algorithm | |
Creates a two-class classification model using the decision forest algorithm | |
Creates a two-class classification model using the decision jungle algorithm | |
Creates a binary classification model using the locally deep Support Vector Machine algorithm | |
Creates a two-class logistic regression model | |
Creates a binary classifier using a neural network algorithm | |
Creates a binary classification model using the Support Vector Machine algorithm | |