BTS Sales Engagement Hub, Oracle Artificial Intelligence (AI)
Regression is a supervised machine learning technique used to predict continuous values based on patterns in data. Unlike classification, which assigns data into categories, regression focuses on estimating numerical outcomes. It looks at the relationship between...BTS Sales Engagement Hub, Oracle Artificial Intelligence (AI)
Attribute importance is a machine learning technique used to determine which variables in a dataset have the greatest influence on a given outcome. While many datasets contain a large number of features, not all of them contribute equally to predictions. Attribute...BTS Sales Engagement Hub, Oracle Artificial Intelligence (AI)
Clustering is an unsupervised machine learning technique that helps find natural groupings within a dataset. Instead of trying to predict a specific outcome, clustering focuses on identifying records that are similar to each other. Data points that share similar...BTS Sales Engagement Hub, Oracle Artificial Intelligence (AI)
Association rules are a type of unsupervised machine learning technique that helps find relationships between items in a dataset. Instead of predicting a specific outcome, the goal is to spot patterns that show how certain items or events tend to occur together. These...BTS Sales Engagement Hub, Oracle Artificial Intelligence (AI)
Anomaly detection is an unsupervised machine learning technique that identifies observations which differ significantly from most of the data. Unlike supervised methods such as classification or regression, anomaly detection does not need labelled outcomes. Instead,...BTS Sales Engagement Hub, Oracle Artificial Intelligence (AI)
Previously, we discussed about what feature extraction is and the algorithms that support it. In this post, the focus shifts to why feature extraction is so useful in real world machine learning scenarios. Drawing from Oracle Machine Learning documentation, feature...
