I\'m using the explorer feature of Weka for classification. So I have my .arff file, with 2 features of NUMERIC value, and my class is a binary 0 or 1 (eg {0,1}).
I\'m doing a research which inv开发者_如何学Goolves \"unsupervised classification\". Basically I have a trainSet and I want to cluster data in X number of classes in unsupervised way. Idea is similar
I do know there are some libraries that allow to use Support vector Machines from python code, but I am looking specifically for libraries that allow one to teach it online (this is, without having to
According to this FAQ the model format in libsvm should be straightforward. And in fact it is, when I call just svm-train. As an example, the first SV for the a1a dataset is
I am playing with some neural network simulations. I\'d like to get two neural networks sharing the input and output nodes (with other nodes being distinct and part of two different routes) to compete
I\'ve been trying to find an answer to this for months (to be used in a machine learning application), it doesn\'t seem like it should be a terribly hard problem, but I\'m a software engineer, and mat
I\'m trying to cluster some images depending on the angles between body parts. The features extracted from each image are:
We have a list of x,y pairs. Every pair represents a point on a 2D space. I want to find the closest point from this list, to a specific point xq,yq. What is the best performance-critical algorithm fo
I am trying to understand the concept of adapter-tuning, prompt-tuning, and prefix-tuning in the context of few-shot learning.
I am building a tweet classification model, and I am having trouble finding a regex pattern that fits what I am looking for.
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