A committee machine is a type of artificial neural network that uses a divide and conquer strategy to combine the responses of multiple neural networks into a single response. This approach is designed to improve the overall performance of the machine learning model by leveraging the strengths of individual models.

• natural language processing
• image classification
• recommendation systems
• decision making under uncertainty

For instance, a committee machine could be trained on a dataset of images, where each image is labeled with one of several classes (e.g. cat, dog, car). The committee machine would consist of multiple neural networks, each trained on a different subset of the images. By combining the responses of these networks, the committee machine can make more accurate predictions than any individual network.

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