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K-Means and its Functions

K-Means and its Functions

by Gabriel Tam | Jul 4, 2026 | BTS Artificial Intelligence (AI), BTS Knowledge Hub

When working with large amounts of data, one of the hardest challenges is not knowing where to start. Data can contain thousands to millions of records, and without clear labels, it can be difficult to understand how those records relate to one another. K-Means...
How does Apriori Work and Benefit Businesses

How does Apriori Work and Benefit Businesses

by Gabriel Tam | Jun 27, 2026 | BTS Artificial Intelligence (AI), BTS Knowledge Hub

When analyzing large datasets, some of the most valuable insights come from discovering relationships that might otherwise go unnoticed. This is where the Apriori algorithm comes in. Supported within Oracle Machine Learning, it is an unsupervised algorithm designed to...
The Use Cases of Generalized Linear Model in Oracle Machine Learning

The Use Cases of Generalized Linear Model in Oracle Machine Learning

by Gabriel Tam | Jun 20, 2026 | BTS Artificial Intelligence (AI), BTS Knowledge Hub

When people think about machine learning, they often focus on advanced algorithms such as neural networks or random forests. However, some of the most useful predictive models are built upon well established statistical techniques. One example is the Generalized...
The Use Cases of Support Vector Machine in Oracle Machine Learning

The Use Cases of Support Vector Machine in Oracle Machine Learning

by Gabriel Tam | Jun 13, 2026 | BTS Artificial Intelligence (AI), BTS Knowledge Hub

Support Vector Machine (SVM) is a supervised machine learning algorithm that can be applied to both classification and regression problems. Its purpose is to detect patterns within data and make predictions by identifying the most effective boundary between different...
The Use Cases of Exponential Smoothing in Oracle Machine Learning

The Use Cases of Exponential Smoothing in Oracle Machine Learning

by Gabriel Tam | Jun 6, 2026 | BTS Artificial Intelligence (AI), BTS Knowledge Hub

Exponential Smoothing is a forecasting algorithm used to analyze time based data and predict future values. It’s particularly useful when data is collected over regular intervals, such as daily sales figures, monthly revenue, or weekly demand. The algorithm works by...
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