• No se han encontrado resultados

Back propagation with balanced MSE cost Function and nearest neighbor editing for handling class overlap and class imbalance

N/A
N/A
Protected

Academic year: 2020

Share "Back propagation with balanced MSE cost Function and nearest neighbor editing for handling class overlap and class imbalance"

Copied!
8
0
0

Texto completo

Loading

Figure

Table 1. Number of training and testing samples in each class
Table 3 shows the overall accuracy and the g-mean obtained with the approaches previously described
Table 4. Performance on each class with the Cost-MLP

Referencias

Documento similar

Instrument Stability is a Key Challenge to measuring the Largest Angular Scales. White noise of photon limited detector

Considering LCC A as the Land Cover Component for land cover class A, and LCC B as the Land Cover Component for land cover class B, Equation 1 is transformed into

For a given fixed power of the halogen lamp, we changed the intensity of the light illuminating the sample object (a small part of an USAF reso- lution test chart with 3.6

SVMs applied to a regression problem perform a linear regression in the feature space using the -insensitive loss as cost function and, at the same time, regularizing the weights

Table 3: Objective values and runtime spent in the search of the optimal solution using cost functions considering fuel and number of UAVs with different percentages.. Cost

These representations capture the nonperturbative information encoded in the dispersion relation for the D–function, the effects due to the interrelation between spacelike and

In both cases, the transitions are attributed classes (shown in red, ma- genta, and green) with high autocorrelation, variance, and MSE compared to the class of the preceding

In particular, different versions of the training set for the base learners can be used, as in bagging (bootstrap sampling of training data), class-switching (noise injection in