Re-exports§
pub use percentile::percentile_rand;percentile-randpub use percentile::median;pub use percentile::percentile;pub use percentile::Fraction;pub use regression::best_fit_ols as regression_best_fit;olspub use regression::Determination;regressionpub use regression::Predictive;regression
Modules§
- percentile
- Percentile / median calculations.
- regression
regression - Various regression models to fit the best line to your data. All written to be understandable.
Structs§
- Cluster
List - A list of clusters.
- F64Ord
Hash - F64 wrapper that implements
OrdandHash. - Owned
Cluster List - Owned variant of
ClusterList. UseSelf::borrowto get aClusterList. The inner slice is accessible through theDerefandDerefMut, which means you can use this as a mutable slice. - Percentiles
Output - Returned from
percentiles_clusterand similar functions. - Standard
Deviation Output - Returned from
standard_deviationand similar functions.
Traits§
- Mean
- Helper-trait for types used by
mean. - Standard
Deviation - Helper-trait for types used by
standard_deviation.
Functions§
- mean
- Mean of
values. - mean_
cluster - Mean of clustered
values. - percentiles_
cluster - Get a collection of percentiles from
values. - standard_
deviation - Get the standard deviation of
values. The mean is also returned from this, because it’s required to compute the standard deviation. - standard_
deviation_ cluster - Get the standard deviation of
values. The mean is also returned from this, because it’s required to compute the standard deviation.
Type Aliases§
- Cluster
As all algorithms are executed in linear time now, this is not as useful, but nevertheless an interesting feature. If you already have clustered data, this feature is great.