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The Use Cases of Exponential Smoothing in Oracle Machine Learning

BTS Sales Engagement Hub, Oracle Artificial Intelligence (AI)

Exponential Smoothing is a forecasting algorithm used to analyse 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...

The Use Cases of Naive Bayes in Oracle Machine Learning

BTS Sales Engagement Hub, Oracle Artificial Intelligence (AI)

Naive Bayes is a supervised machine learning algorithm consisting of three main types (Gaussian, Multinomial & Bernoulli). This probability-based algorithm is mainly used for classification tasks by using the relationships between different features to predict the...

The Use Cases of Random Forest in Oracle Machine Learning

BTS Sales Engagement Hub, Oracle Artificial Intelligence (AI)

Random Forest is a supervised machine learning algorithm used for both classification and regression tasks. It is based on the idea of combining multiple decision trees to produce a stronger and more reliable model. Instead of relying on a single tree, Random Forest...

The Use Cases of Minimum Description Length in Oracle Machine Learning

BTS Sales Engagement Hub, Oracle Artificial Intelligence (AI)

Minimum Description Length, often shortened to MDL, is a principle used in machine learning and data analysis to help identify models that best explain a dataset while avoiding unnecessary complexity. The main idea behind MDL is that the best model is one that...

The Use Cases of Neural Networks in Oracle Machine Learning

BTS Sales Engagement Hub, Oracle Artificial Intelligence (AI)

Neural networks are a machine learning technique inspired by the way the human brain processes information. They are designed to recognise patterns, learn from data, and make predictions by analysing relationships between inputs and outputs. Neural networks are...
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