query: SVM One-vs-One vs One-vs-ALL SVM
positive_passages.docid: 26160
positive_passages.text: One-vs-All and One-vs-One in svm?
negative_passages.docid: 72077
negative_passages.text: ''Linear'' transformations between vector spaces over different fields .
negative_passages.docid: 149452
negative_passages.text: One definition rule and different class definitions in two translation units
negative_passages.docid: 35960
negative_passages.text: Testing the difference in AIC of two non-nested models
negative_passages.docid: 15062
negative_passages.text: How connection helps us to identify two different vector spaces?
negative_passages.docid: 107608
negative_passages.text: Differentiation in support vector machine
negative_passages.docid: 124976
negative_passages.text: How to do one-class text classification?
negative_passages.docid: 95555
negative_passages.text: Should I normalize word2vec's word vectors before using them?
negative_passages.docid: 145143
negative_passages.text: What is the difference between a multi-label and a multi-class classification?
negative_passages.docid: 48283
negative_passages.text: Feature selection and cross-validation
negative_passages.docid: 15196
negative_passages.text: Why scaling is important for the linear SVM classification?
negative_passages.docid: 79824
negative_passages.text: Varied Activation Functions in Neural Networks
negative_passages.docid: 81007
negative_passages.text: Help me understand Support Vector Machines
negative_passages.docid: 91111
negative_passages.text: Which performance measure to use when using SVM: MSE or MAE?
negative_passages.docid: 153261
negative_passages.text: Linear kernel and non-linear kernel for support vector machine?
negative_passages.docid: 48846
negative_passages.text: "All X" vs. "all of X" vs. "all the X"
negative_passages.docid: 141640
negative_passages.text: Sklearn - Choosing the right model for supervised learning/classification task