query: Curse of dimensionality- does cosine similarity work better and if so, why?
positive_passages.docid: 115109
positive_passages.text: Euclidean distance is usually not good for sparse data (and more general case)?
negative_passages.docid: 142784
negative_passages.text: For linear classifiers, do larger coefficients imply more important features?
negative_passages.docid: 138597
negative_passages.text: What is the justification for Rayleigh's method of dimensional analysis?
negative_passages.docid: 62974
negative_passages.text: Extended Euclidean Algorithm: why does it work?
negative_passages.docid: 14183
negative_passages.text: Why Lasso or ElasticNet perform better than Ridge when the features are correlated
negative_passages.docid: 60914
negative_passages.text: Square bracket notation for dimensions and units: usage and conventions
negative_passages.docid: 29381
negative_passages.text: How to perform dimensionality reduction with PCA in R
negative_passages.docid: 46740
negative_passages.text: Transforming proportion data: when arcsin square root is not enough
negative_passages.docid: 70917
negative_passages.text: What's the difference between principal component analysis and multidimensional scaling?
negative_passages.docid: 24132
negative_passages.text: Why does Gaussian elimination not preserve similarity of a matrix?
negative_passages.docid: 12213
negative_passages.text: Similarity of real matrices over $\mathbb{C}$
negative_passages.docid: 30889
negative_passages.text: Classifying complex $2\times 2$ matrices up to similarity
negative_passages.docid: 57060
negative_passages.text: Is normalizing the features always good for classification?
negative_passages.docid: 114612
negative_passages.text: Why is "consistent nearest neighbour" Non-parametric?
negative_passages.docid: 34931
negative_passages.text: How to understand "nonlinear" as in "nonlinear dimensionality reduction"?
negative_passages.docid: 123334
negative_passages.text: When do we combine dimensionality reduction with clustering?
negative_passages.docid: 11188
negative_passages.text: Can principal component analysis be applied to datasets containing a mix of continuous and categorical variables?