Hi, maybe I overlooked something, but I couldn't find the classic adaline (ADAptive LInear NEuron) in scikit-learn. It's probably not that useful (anymore) since we have logistic regression and support vector machines, but maybe it would not be a bad idea to add for the sake of completeness (and since scikit-learn also has a perceptron)?
The implementation would be similar to logistic regression, but the cost function is the sum of the squared errors like in linear regression. It could be added to the SGDClassifier as loss='linear' or loss='adaline' plus a separate implementation using liblinear. The reference would be: B. Widrow et al. Adaptive ”Adaline” neuron using chemical ”memistors”. Number Technical Report 1553-2. Stanford Electron. Labs., Stanford, CA, October 1960 What do you think? Best, Sebastian ------------------------------------------------------------------------------ Dive into the World of Parallel Programming The Go Parallel Website, sponsored by Intel and developed in partnership with Slashdot Media, is your hub for all things parallel software development, from weekly thought leadership blogs to news, videos, case studies, tutorials and more. Take a look and join the conversation now. http://goparallel.sourceforge.net/ _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
