cornac 0.1.0

A collection of recommendation algorithms and comparisons

Cornac

Cornac is python recommender system library for easy, effective and efficient experiments. Cornac is simple and handy. It is designed from the ground-up to faithfully reflect the standard steps taken by researchers to implement and evaluate personalized recommendation models.

Quick links

Website | Documentation | Preferred.AI

Getting started: your first Cornac experiment

This example will show you how to run your very first experiment using Cornac.

Load the MovieLens 100K dataset (will be automatically downloaded if not cached).

from cornac.datasets import MovieLens100K

ml_100k = MovieLens100K.load_data()

Instantiate an evaluation strategy.

from cornac.eval_strategies import RatioSplit

ratio_split = RatioSplit(data=ml_100k, test_size=0.2, rating_threshold=4.0, exclude_unknowns=False)

Instantiate models that we want to evaluate. Here we use Probabilistic Matrix Factorization (PMF) as an example.

pmf = cornac.models.PMF(k=10, max_iter=100, learning_rate=0.001, lamda=0.001)

Instantiate evaluation metrics.

mae = cornac.metrics.MAE()
rmse = cornac.metrics.RMSE()
rec_20 = cornac.metrics.Recall(k=20)
pre_20 = cornac.metrics.Precision(k=20)

Instantiate and then run an experiment.

exp = cornac.Experiment(eval_strategy=ratio_split,
                        models=[pmf],
                        metrics=[mae, rmse, rec_20, pre_20],
                        user_based=True)
exp.run()

Output

          MAE      RMSE  Recall@20  Precision@20
PMF  0.760277  0.919413   0.081803        0.0462

For more details, please take a look at our examples.

Installation

Currently, we are supporting Python 3 (version 3.6 is recommended), please make sure that you are on the latest pip. Then, run the appropriate Cornac install command according to your platform.

• Linux:

   pip3 install https://github.com/PreferredAI/cornac/archive/master.zip --process-dependency-links
  

• MacOS:

  • You will need to install the Torch dependency first. Please follow the instructions here to install PyTorch on MacOS using conda. Then run the following command.

   pip3 install https://github.com/PreferredAI/cornac/archive/master.zip
  

• Windows:

   # Installing PyTorch is required as this dependency is not handle automatically.
   pip3 install https://download.pytorch.org/whl/cpu/torch-1.0.0-cp36-cp36m-win_amd64.whl
   pip3 install https://github.com/PreferredAI/cornac/raw/master/dist/cornac-0.1.0-cp36-cp36m-win_amd64.whl
  

License

Apache License 2.0