vasco
discover hidden correlations in your data with MIC
Repository
Florents-Tselai/vasco
https://github.com/Florents-Tselai/vasco
Source
vasco-0.1.0.tar.gz
vasco-0.1.0.tar.gz
Overview
| ID | Extension | Bin | Lib | Load | Create | Trust | Reloc | Schema |
|---|---|---|---|---|---|---|---|---|
| 4660 | vasco | No | Yes | No | Yes | No | Yes | - |
| Related | weighted_statistics pg_math xicor fbsql |
|---|
Version
| Type | Repo | Version | PG Ver | Package | Deps |
|---|---|---|---|---|---|
| EXT | PIGSTY | 0.1.0 | 1817161514 | vasco | - |
| RPM | PIGSTY | 0.1.0 | 1817161514 | vasco_$v | - |
| DEB | PIGSTY | 0.1.0 | 1817161514 | postgresql-$v-vasco | - |
Build
You can build the RPM / DEB packages for vasco using pig build:
Install
You can install vasco directly. First, make sure the PGDG and PIGSTY repositories are added and enabled:
Install the extension using pig or apt/yum/dnf:
Install
pig
dnf
apt
Create Extension:
Usage
vasco: Maximal Information Coefficient (MIC) extension for PostgreSQL
Discover hidden correlations in your data using the Maximal Information Coefficient (MIC) and the MINE family of statistics.
Aggregate Functions
| Function | Description |
|---|---|
mic(x, y) | Maximal Information Coefficient – detects any relationship |
mas(x, y) | Maximum Asymmetry Score – deviation from monotonicity |
mev(x, y) | Maximum Edge Value – degree of continuous function sampling |
mcn(x, y) | Minimum Cell Number – complexity of association |
mcn_general(x, y) | MCN with eps = 1 - MIC |
tic(x, y) | Total Information Coefficient |
gmic(x, y) | Generalized Mean Information Coefficient |
Utility Functions
| Function | Description |
|---|---|
vasco_corr_matrix(table_name, output_table) | Compute MIC for all column pairs and store as a correlation matrix table |
Configuration
Examples
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