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Commit ade7684e authored by shamith2's avatar shamith2
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Update README.md

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......@@ -11,6 +11,10 @@ processes.
```console
$ git clone https://github.com/shamith2/BayesianOptimization.git
pip install --upgrade pip
pip install numpy
pip install scipy
pip install scikit-learn
```
This is a constrained global optimization package built upon bayesian inference
......@@ -19,7 +23,7 @@ function in as few iterations as possible. This technique is particularly
suited for optimization of high cost functions, situations where the balance
between exploration and exploitation is important.
Copyright : https://github.com/fmfn/BayesianOptimization
Adapted from : https://github.com/fmfn/BayesianOptimization
## Quick Start
For a quick tour over the basics of the Bayesian Optimization package and More detailed information, other advanced features, and tips on usage/implementation can be found in the [examples](https://github.com/fmfn/BayesianOptimization/tree/master/examples) folder.
......@@ -259,49 +263,6 @@ from bayes_opt.plotter import JSONPlotter
JSONPlotter(log_file, plot_file, func, x_eval=False)
```
## Next Steps
This introduction covered the most basic functionality of the package. Checkout the [basic-tour](https://github.com/fmfn/BayesianOptimization/blob/master/examples/basic-tour.ipynb) and [advanced-tour](https://github.com/fmfn/BayesianOptimization/blob/master/examples/advanced-tour.ipynb) notebooks in the example folder, where you will find detailed explanations and other more advanced functionality. Also, browse the examples folder for implementation tips and ideas.
Installation
============
### Installation
The latest release can be obtained by two ways:
* With PyPI (pip):
pip install bayesian-optimization
* With conda (from conda-forge channel):
conda install -c conda-forge bayesian-optimization
The bleeding edge version can be installed with:
pip install git+https://github.com/fmfn/BayesianOptimization.git
If you prefer, you can clone it and run the setup.py file. Use the following
commands to get a copy from Github and install all dependencies:
git clone https://github.com/fmfn/BayesianOptimization.git
cd BayesianOptimization
python setup.py install
Citation
============
If you used this package in your research and is interested in citing it here's how you do it:
```
@Misc{,
author = {Fernando Nogueira},
title = {{Bayesian Optimization}: Open source constrained global optimization tool for {Python}},
year = {2014--},
url = " https://github.com/fmfn/BayesianOptimization"
}
```
# Dependencies
* Numpy
......
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