README
¶
stats
There are several packages here for operating on vector, tensor, and table data, for computing standard statistics and performing related computations, such as normalizing the data.
- clust implements agglomerative clustering of items based on simat similarity matrix data.
- convolve convolves data (e.g., for smoothing).
- glm fits a general linear model for one or more dependent variables as a function of one or more independent variables. This encompasses all forms of regression.
- histogram bins data into groups and reports the frequency of elements in the bins.
- metric computes similarity / distance metrics for comparing two vectors
- norm normalizes vector data
- pca computes principal components analysis (PCA) or singular value decomposition (SVD) on correlation matricies, which is a widely-used way of reducing the dimensionality of high-dimensional data.
- simat computes a similarity matrix for the metric similarity of two vectors.
- split provides grouping and aggregation functions operating on
table.Tabledata, e.g., like a "pivot table" in a spreadsheet. - stats provides a set of standard summary statistics on a range of different data types, including basic slices of floats, to tensor and table data.
Directories
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| Path | Synopsis |
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Package metric provides various similarity / distance metrics for comparing floating-point vectors.
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Package metric provides various similarity / distance metrics for comparing floating-point vectors. |
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Package norm provides normalization and norm metric computations e.g., L2 = sqrt of sum of squares of a vector.
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Package norm provides normalization and norm metric computations e.g., L2 = sqrt of sum of squares of a vector. |
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Package pca performs principal component's analysis and associated covariance matrix computations, operating on table.Table or tensor.Tensor data.
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Package pca performs principal component's analysis and associated covariance matrix computations, operating on table.Table or tensor.Tensor data. |
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Package simat provides similarity / distance matrix functions that create a SimMat matrix from Tensor or Table data.
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Package simat provides similarity / distance matrix functions that create a SimMat matrix from Tensor or Table data. |
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Package split provides GroupBy, Agg, Permute and other functions that create and populate Splits of table.Table data.
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Package split provides GroupBy, Agg, Permute and other functions that create and populate Splits of table.Table data. |
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Package agg provides aggregation functions operating on IndexView indexed views of table.Table data, along with standard AggFunc functions that can be used at any level of aggregation from tensor on up.
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Package agg provides aggregation functions operating on IndexView indexed views of table.Table data, along with standard AggFunc functions that can be used at any level of aggregation from tensor on up. |
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