In these previous posts:

- AdaOpt classification on MNIST handwritten digits (without preprocessing) (on 05/29/2020)
- AdaOpt (a probabilistic classifier based on a mix of multivariable optimization and nearest neighbors) for R (on 05/22/2020)
- AdaOpt (on 05/15/2020)

I introduced `AdaOpt`

, a novel *probabilistic* classifier based on a **mix of multivariable optimization and a nearest neighbors** algorithm. More details about the algorithm can also be found in this (short) paper.

`mlsauce`

’s development version now contains a **parallel implementation**of

`AdaOpt`

. In order to install this development version from the command line, you’ll need to type:```
pip install git+https://github.com/thierrymoudiki/mlsauce.git --upgrade
```

And in order to use parallel processing, create the `AdaOpt`

object (see previous post) with:

```
n_jobs = 2 # or 4, or -1 or 13
```