What is the goal of the 'Optimize Training Set' feature in an Analytics index?

The goal of the 'Optimize Training Set' feature in an Analytics index is to include only conceptually valuable documents from the training data source. This feature focuses on refining the dataset used for training by filtering out irrelevant or less useful documents, ensuring that the training set reflects the most pertinent information. By doing so, it enhances the overall performance of the analytics process, allowing for more accurate and relevant results in the analysis of documents. This is especially important in the context of machine learning and data mining, where the quality of the training data directly impacts the effectiveness of the models being developed.

In contrast, including all documents from the saved search would create a larger training set, but it may incorporate numerous documents that do not contribute meaningfully to training and can even obscure important insights. Increasing the number of dimensions in the concept space does not necessarily align with the purpose of optimizing the training set, as it can complicate the analysis without guaranteeing the inclusion of valuable data. Lastly, simply increasing the size of the index doesn't address the concept of value in the training documents, which is the primary focus of optimization.