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Variable dimension data? • /r/MachineLearning

@machinelearnbotApr-18-2016, 00:30:20 GMT

You could do K-nearest neighbor's interpolation to give the empty 0 values a "guess" to how they would look like to the nearest neighbors. How well this would work is really just based on the properties of the data. If dimension k can be predicted by some association with a dimension j, and this relationship with k and j is fairly strong throughout the data, then it's worth trying. If it's all over the place, this hack won't help at all, perhaps it would even make very unreliable predictions.

artificial intelligence, machine learning, variable dimension data, (2 more...)

@machinelearnbot

Technology: Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning > Nearest Neighbor Methods (0.75)

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