query: Extraction of a decision boundary (LDA) after a systematic querying of the feature space and convolution with Sobel filter (examples in numpy)
positive_passages.docid: 155834
positive_passages.text: Compute and graph the LDA decision boundary
negative_passages.docid: 145973
negative_passages.text: Identifying critical points/lines of 2/3D image/cubes
negative_passages.docid: 142959
negative_passages.text: Do we still need to do feature selection while using Regularization algorithms?
negative_passages.docid: 32420
negative_passages.text: A complete orthonormal system contained in a dense sub-space.
negative_passages.docid: 91938
negative_passages.text: Countable Matrix Representation
negative_passages.docid: 49026
negative_passages.text: How to find circular objects in an image?
negative_passages.docid: 115584
negative_passages.text: Dataset transformation for clustering after PCA
negative_passages.docid: 63996
negative_passages.text: How to derive a ranking function by analysing feature correlations
negative_passages.docid: 145438
negative_passages.text: "Kernel density estimation" is a convolution of what?
negative_passages.docid: 156676
negative_passages.text: How to compare features and classifiers which achieve perfect accuracy?
negative_passages.docid: 102785
negative_passages.text: Analysis of Kullback-Leibler divergence
negative_passages.docid: 17765
negative_passages.text: How to use SVD for dimensionality reduction to reduce the number of columns (features) of the data matrix?
negative_passages.docid: 138904
negative_passages.text: Recursive feature elimination and one-hot & dummy encoding?
negative_passages.docid: 70887
negative_passages.text: Applications of ultrafilters
negative_passages.docid: 8657
negative_passages.text: Generating a DEM and DSM from correct LiDAR point classification
negative_passages.docid: 143724
negative_passages.text: Is it possible to use kernel PCA for feature selection?
negative_passages.docid: 90679
negative_passages.text: Algebra of LDA. Fisher discrimination power of a variable and Linear Discriminant Analysis