Wildboar

Latest version: v1.2.1

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0.3.4

Changed

* Complete rewrite of the shapelet tree representation to allow releasing GIL.
The prediction of trees should be backwards compatible, i.e., trees fitted using
the new versions are functionally equivalent to the old but with another internal
representation.

0.3.3

Fixes

* Binary builds

0.3.2

Fixed

* Improved caching of lower-bound for DTW
The DTW subsequence search implementation has been improved by caching
DTW lower-bound information for repeated calls with the same
subsequece. This slightly increases the memory requirement, but can
give significantly improved performance under certain circumstances.

* Allow shapelet information to be extracted
A new attribute `ts_info` is added to `Shapelet` (which is accessible
from `tree.root_node_.shapelet`). `ts_info` returns a tuple
`(ts_index, ts_start, length)` with information about the index (in
the `x` used to fit, `fit(x, y)`, the model) and the start position of
the shapelet. For a shapelet tree/forest fit on `x` the shapelet in a
particular node is given by `x[ts_index, ts_start:(ts_start + length)]`.

0.3

Added
* Regression shapelet trees
A new type of shapelet trees has been added.
`wildboar.tree.ShapeletTreeRegressor` which allows for constructing shapelet
trees used to predict real value outputs.

* Regression shapelet forest
A new tyoe of shapelet forest has been added.
`wildboar.ensemble.ShapeletForestRegressor` which allows for constructing
shapelet forests for predicting real value outputs.

Fixed

* a6f656d Fix bug for strided labels not correctly accounted for
* 321a04d Remove unused property `unscaled_threshold`

0.2

Information
* Stability: beta
* Release data: 2019-05-23

Installation
* `pip install -r requirements.txt`
* `pip setup.py install`

Usage

from wildboar.ensemble import ShapeletForestClassifier
c = ShapeletForestClassifier(n_estimators=100, metric="scaled_euclidean")
c.fit(X, y)
c.predict(X_test)

Changelog
* major: add regression shapelet tree: `ShapeletTreeRegressor` and `ShapleletForestRegressor`
* fix: striding bug with labels
* fix: bug 1
* fix: issue 2
* fix: remove unused property `scaled_threshold`

0.1

* First public release
* Added: `ShapeletTreeClassifier` - a generic shapelet tree implementation for constructing random shapelet trees
* Added: Distance computations (for sliding distances):
- Fast Euclidean distance
- Fast z-normalized Euclidean distance
- Fast bounded and z-normalized dynamic time warping distance (with all optimizations from the UCRSuite)
* Added: API for finding the best matching positions and the positions within a given threshold

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