Methods and principles of building "computer systems that automatically improve with experience."

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How would you represent this one-vs-all SVM accuracy?

I have a set on one-vs-all SVMs. Let's say I have three classes. I want to show FAR and FRR from the system, but I appear to get getting very large FRR values and very little FAR values. This is ...
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Using von Mises-Fisher distributions for geo-spatial machine learning

There's an interesting paper about predicting the geographical co-ordinates of Twitter users based on the kinds of words that they use in their posts. I'd like to do something similar that involves ...
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Similarity of two neural networks

I have two neural networks. If I take only weights (the activation functions for both are the same), is there a way to tell the percent similarity of these two networks?
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Extrapolating from a filtered data set

Imagine the following hypothetical machine learning for classifying benign/malignant cancer tumors. The doctors want to minimize the number of patients they call in for tests. They had an original ...
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On the importance of the i.i.d. assumption in statistical learning

In statistical learning, implicitly or explicitly, one always assumes that the training set $\mathcal{D} = \{ \bf {X}, \bf{y} \}$ is composed of $N$ input/response tuples $({\bf{X}}_i,y_i)$ that are ...
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Can (loopy) belief propagation be used to learn from a data set?

I'm trying to expand my experience with restricted Boltzmann machines to a more general class of graphical models and currently learning about belief propagation using message passing algorithms. One ...