data.frame(x = 1:4, y = 1:2) ## x y ## 1 1 1 ## 2 2 2 ## 3 3 1 ## 4 4 2 data.frame(x = 1:4, y = 1:3) ## Error in data.frame(x = 1:4, y = 1:3) : 参数值意味着不同的行数: 4, 3 tibble(x = 1:4, y = 1) ## # A tibble: 4 x 2 ## x ...
ChristianN.S.PedersenT. G. Kristensen and C. N. S. Pedersen. Data structures for accelerating Tanimoto queries on real valued vectors. In V. Moulton and M. Singh, editors, WABI, volume 6293 of Lecture Notes in Computer Science, pages 28-39. Springer, 2010....
NumPy is the foundation of the Python machine learning stack. NumPy allows for efficient operations on the data structures often used in machine learning: vectors, matrices, and tensors. While NumPy is not the focus of this book, it will show up frequently throughout the following chapters. Th...
We derive the test statistics under the assumption that the covariance matrices follow a diagonal matrix structure. In comparison with the diagonal Hotelling's tests, our proposed test statistics display some interesting characteristics. In particular, they are a summation of the log-transformed squared...
Usingsvdsis not the most efficient way to find a few singular values of small, dense matrices. For such problems, usingsvd(full(A))might be quicker. For example, finding three singular values in a 500-by-500 matrix is a relatively small problem thatsvdcan handle easily. ...
The library can be imported in the usual ways: importexclusivefromexclusiveimport* Examples This library makes it possible to concisely construct multiple XOR-based secret shares from a bytes-like object: >>>fromexclusiveimportshares,xor>>>(a,b)=shares(bytes([1,2,3]))>>>(c,d)=shares(byte...
In particular, Cao et al. have utilized a state-of-the-art embedding method, GEEK (‘Gene Expression Embedding frameworK’), to combine biological networks and omics data with the metapath concept1, and have produced interpretable biological knowledge such as gene function, protein complex, ...
keep the original vectors. This generally comes at the cost of a less precise search but these methods can scale to billions of vectors in main memory on a single server. Other methods, like HNSW and NSG add an indexing structure on top of the raw vectors to make searching more efficient...
could be used in the future for a variety of gene therapies and personalized medicine. To our knowledge, this is the first report on designing such lipid-coated phage AVVs that, considering the abundance of phage nanostructures in nature, would open new avenues for creating novel delivery ...
The simplest and most common data structure in R is the vector. Vectors come in two different flavors: atomic vectors and lists. An atomic vector contains exactly one data type, whereas a list may contain multiple data types. We'll explore atomic vectors further before we get to lists. ...