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Cette fonction permet de projeter chaque objet de l’ensemble de données dans un graphique 2D, en utilisant un marqueur de couleur lorsque les étiquettes des classes sont

dataset Define dataset from data matrix and labels gendat Generate a random subset of a dataset genlab Generate dataset labels.. seldat Select a specify subset of

For example, quadratic classifier assuming Gaussian densities (qdc), returns class conditional densities as soft outputs.. In 2D feature spaces, we can visualize the classifiers

Alternatively, you can set the operating point in sdroc object manually (r=setcurop(r,30)) We can now estimate the confusion matrix on the test set:..

So, cmaps begins with data normalization by variance, then computes a Euclidean distance matrix which is fed into the classical scaling routine to derive a projected space in 15D. To

If the so-called base classifiers ( w1, w2,. .) do not output posterior probabilities, but for instance distances to the classifier boundaries, then these combining rules

>> c = spatm(b,2) % spatial mapping using smoothing of sigma = 2.0 16384 by 6 dataset with 1 class: [16384]. Let us visualise the resulting dataset c

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