Classifying Skewed Data: Importance Weighting to Optimize Average Recall Andrew Rosenberg1 1 Department of Computer Science, Queens College (CUNY), Flushing, NY, USA

First Page		Document Content
Date: 2012-10-22 02:42:52 Statistical classification Machine learning Ensemble learning Data mining K-nearest neighbors algorithm Multiclass classification Boosting Pitch accent Support vector machine AdaBoost Receiver operating characteristic Binary classification		Classifying Skewed Data: Importance Weighting to Optimize Average Recall Andrew Rosenberg1 1 Department of Computer Science, Queens College (CUNY), Flushing, NY, USA Add to Reading List Source URL: speech.cs.qc.cuny.edu Download Document from Source Website File Size: 163,41 KB Share Document on Facebook

	Support Vector Machine Mohammad Emtiyaz Khan EPFL Oct 29, 2015 DocID: 1uEDY - View Document
	Support Vector Machines and Kernel Methods Shrey Gupta Applied Machine Learning (HOUSECS 59-01), Duke University October 10, 2018 DocID: 1uA0f - View Document
	Robust Truncated Hinge Loss Support Vector Machines Yichao W U and Yufeng L IU The support vector machine (SVM) has been widely applied for classification problems in both machine learning and statistics. Despite its pop DocID: 1uuGd - View Document
	Support Vector Machine for Anti-Pattern Detection Abdou Maiga1,3 , Nasir Ali1,2 , Neelesh Bhattacharya1,2 , Aminata Sabané1,2 Yann-Gaël Guéhéneuc1 , Giuliano Antoniol2 , and Esma Aimeur3 1 Ptidej Team, DGIGL, École DocID: 1tZPb - View Document
	Support Vector Machine Mohammad Emtiyaz Khan EPFL Oct 29, 2015 DocID: 1tVBH - View Document