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fixed structures

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0xflotus
2018-12-30 03:17:50 +01:00
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commit 52f6beba35
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@@ -472,7 +472,7 @@ optionally be separated so Rosenstraße and Rosen Straße are equivalent.
for a wide variety of countries and languages, not just US/English.
The model is trained on over 1 billion addresses and address-like strings, using the
templates in the [OpenCage address formatting repo](https://github.com/OpenCageData/address-formatting) to construct formatted,
tagged traning examples for every inhabited country in the world. Many types of [normalizations](https://github.com/openvenues/libpostal/blob/master/scripts/geodata/addresses/components.py)
tagged training examples for every inhabited country in the world. Many types of [normalizations](https://github.com/openvenues/libpostal/blob/master/scripts/geodata/addresses/components.py)
are performed to make the training data resemble real messy geocoder input as closely as possible.
- **Language classification**: multinomial logistic regression
@@ -623,7 +623,7 @@ libpostal is written in modern, legible, C99 and uses the following conventions:
- Confines almost all mallocs to *name*_new and all frees to *name*_destroy
- Efficient existing implementations for simple things like hashtables
- Generic containers (via [klib](https://github.com/attractivechaos/klib)) whenever possible
- Data structrues take advantage of sparsity as much as possible
- Data structures take advantage of sparsity as much as possible
- Efficient double-array trie implementation for most string dictionaries
- Cross-platform as much as possible, particularly for *nix