… Maximin classifier, which conducts optimization based on the … a new Linear Max K-min
(LMKM) classifier for 2-class classification problems, which offers a general classification solution …

… linear classifier (Dong et al. 2012), in this paper, we propose a general Maximum K-Min …
of the K worst instances, Maximum K-Min Gain/Minimum K-Max Loss (MKM) criterion is firstly in…

… one-dimensional max-k-min subspace can be accurately and efficiently obtained by linear …
For quantitative comparison, we measure the classification error using nearest mean classifier …

… 1) Classification Modeling: The ML classification models … of 2-D convolutional and max
pooling layers, three fully connected … In this study, the Lasso and linear SVR models were linear, …

… classification performance was verified through four different test roads. The proposed
network shows the classification … classifier and controls speed of the vehicle with respect to the …

… TDA is a generalization of the classical linear discriminant … classification accuracy and
interpretability of the classifier; see … maximum norm. The Frobenius norm is always larger than the …

… Such a classifier was recently studied for a standard novelty detection task [19], and …
classification models. A confidence score about novelty can be measured by taking the maximum …

… Also, nearest neighbor, Naive bayes boost, linear SVM etc. were used as a classifier. Lastly,
A.Valada et al. [12] used audio waveform as a feature to terrain classification problem. Fast …

… element analysis using the UDEC code, with the linear size of triangular zones varying from
0.002 to 0.1 m (Fig. 9). The maximum number of internal zones to be analyzed for this study …

… classifiers consistently perform better than linear classifiers on vision tasks. In particular we
can train our piece-wise linear additive classifier … Dalal & Triggs’ linear detector (based on …