Re-exports§
pub use percentile::percentile_rand;
percentile-rand
pub use percentile::median;
pub use percentile::percentile;
pub use percentile::Fraction;
pub use regression::best_fit_ols as regression_best_fit;
ols
pub use regression::Determination;
regression
pub 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
Ord
andHash
. - Owned
Cluster List - Owned variant of
ClusterList
. UseSelf::borrow
to get aClusterList
. The inner slice is accessible through theDeref
andDerefMut
, which means you can use this as a mutable slice. - Percentiles
Output - Returned from
percentiles_cluster
and similar functions. - Standard
Deviation Output - Returned from
standard_deviation
and 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.