Optimization

Optimization tasks solve problems related to optimizing a situation, given an objective function and a set of constraints.

• Mixed Integer Linear Programming

• Network Optimizer

Supervised

In supervised learning problems an output attribute is present in the dataset and the target of the analysis is to derive a model that describes the relationship between this output attribute and other input attributes in the dataset.

• Decision Tree

• K-Nearest Neighbor Classification

• Logic Learning Machine Classification

• Logistic

• Neural Networks Classification

• Classification SVM

• Auto Regressive

• K-Nearest Neighbor Regression

• Linear

• Logic Learning Machine Regression

• Neural Networks Regression

• Regression SVM

• Regression Tree

• Logic Learning Machine One-class

Unsupervised

In unsupervised learning problems no output variables are present, and examples included in the dataset are partitioned into a number of groups (clusters), according to a given measure of similarity: two examples belonging to the same group must exhibit a higher value of similarity than two patterns associated with different clusters.

• Label Clustering

• Projection Clustering

• Standard Clustering

• Anomaly Detection

• Assortment Optimizer

• Frequent Itemsets Mining

• Hierarchical Basket Analysis

• Sequence Analysis

• Similar Items Detector