In order to discriminate between genuine and fake coins, we train a classifier using the subspace representations. A thorough evaluation of the proposed intelligent system has been conducted on four coin dataset
My second question when I use PCA on the whole matrix say for example 302*8100 rows and columns , I get a result 8100*301 which messes up the dimension. Should I use the coeff or should i use the score variable to obtain the reduced dimension...
–Test set: A set of examples used only to assess the performance of a fully-specified classifier. — Brian Ripley, page 354, Pattern Recognition and Neural Networks, 1996 These are the recommended definitions and usages of the terms. A good example that these definitions are canonical is thei...
Histogram difference refers to a measure used in computer science to detect similarity between images by comparing changes in the weighted color histogram of the images. It is less sensitive to subtle motion and can be used to limit distortion caused by noise and motion in sub-regions of the ...
binormal modelconditional and marginal inferencemonte carlo methodspaired samplesSplus/R routinesThe maximum vertical distance between a receiver operating characteristic (ROC) curve and its chance diagonal is a common measure of effectiveness of the classifier that gives rise to this curve. This measure...
This algorithm is a type of linear classifier that takes vector as an input, and calculates the linear combination: (1) for a weight vector and a bias . After that, we apply the step function: (2) Formally, the model that we defined with one neuron and step activation function is ...
Finally, note that B corresponds to the boundary be- tween the adversarial and the estimated true class, and thus it can be seen as an affine binary classifier. Since at each iteration the adversarial class is computed as the closest (in an `2 sense) to the true one, we can say t...
But the results i am getting are totally different. Where the second models performs way better than the first. Is it expected ? First model gives accuracy of 57% where the second model gives 80% accuracy. The first model is checkpoint file. For transfer learning, i have converted the chec...
Finally, we can have a framework-like integration, for example, Spring Data JPA, with pre-defined interfaces to access entities but still using JPA and an entity manager under the hood. In this tutorial, we’ll talk about the difference between Spring Data JPA and JPA. We’ll also explain...
Here we will use tf.layers and tf.contrib.learn to build our CNN classifier. The code follows theofficial tutorial on tf.layers: So, both TensorFlow and PyTorch provide usefulabstractionsto reduce amounts of boilerplate code and speed up model development. The main difference between them is ...