What tool can be used in SAS Enterprise Miner to explore different network architectures and hidden unit counts?

The appropriate tool for exploring different network architectures and hidden unit counts in SAS Enterprise Miner is AutoNeural. This tool is specifically designed for automating the configuration of neural networks, allowing users to efficiently test various architectures and configurations without manually altering each parameter.

AutoNeural simplifies the experimentation process by automatically identifying the optimal settings, including the number of hidden units and layers, based on performance metrics on training and validation datasets. This capability makes it particularly useful for practitioners who wish to optimize their neural network models without getting bogged down in extensive manual configuration.

In contrast, other options serve different purposes. The DMNeural tool provides a more traditional setup for building neural networks but lacks the automated feature of exploring various network configurations. The general Neural Network tool, while capable of modeling neural networks, does not inherently provide the automation aspect that AutoNeural offers for architectural exploration. Rule Induction, on the other hand, focuses on deriving rules from data rather than modeling neural network architectures, making it unrelated to the specific task at hand.

Hence, AutoNeural stands out as the correct choice for exploring different network architectures and hidden unit counts effectively.