Source code for cornac.experiment.experiment

# Copyright 2018 The Cornac Authors. All Rights Reserved.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================

import os
from datetime import datetime

from .result import ExperimentResult
from .result import CVExperimentResult
from ..metrics.rating import RatingMetric
from ..metrics.ranking import RankingMetric
from ..models.recommender import Recommender

[docs]class Experiment: """ Experiment Class Parameters ---------- eval_method: :obj:`<cornac.eval_methods.BaseMethod>`, required The evaluation method (e.g., RatioSplit). models: array of :obj:`<cornac.models.Recommender>`, required A collection of recommender models to evaluate, e.g., [C2PF, HPF, PMF]. metrics: array of :obj:{`<cornac.metrics.RatingMetric>`, `<cornac.metrics.RankingMetric>`}, required A collection of metrics to use to evaluate the recommender models, \ e.g., [NDCG, MRR, Recall]. user_based: bool, optional, default: True This parameter is only useful if you are considering rating metrics. When True, first the average performance \ for every user is computed, then the obtained values are averaged to return the final result. If `False`, results will be averaged over the number of ratings. show_validation: bool, optional, default: True Whether to show the results on validation set (if exists). save_dir: str, optional, default: None Path to a directory for storing trained models and logs. If None, models will NOT be stored and logs will be saved in the current working directory. Attributes ---------- result: array of :obj:`<cornac.experiment.result.Result>`, default: None This attribute contains the results per-model of your experiment on the test set, initially it is set to None. val_result: array of :obj:`<cornac.experiment.result.Result>`, default: None This attribute contains the results per-model of your experiment on the validation set (if exists), initially it is set to None. """ def __init__( self, eval_method, models, metrics, user_based=True, show_validation=True, verbose=False, save_dir=None, ): self.eval_method = eval_method self.models = self._validate_models(models) self.metrics = self._validate_metrics(metrics) self.user_based = user_based self.show_validation = show_validation self.verbose = verbose self.save_dir = save_dir self.result = None self.val_result = None @staticmethod def _validate_models(input_models): if not hasattr(input_models, "__len__"): raise ValueError( "models have to be an array but {}".format(type(input_models)) ) valid_models = [] for model in input_models: if isinstance(model, Recommender): valid_models.append(model) return valid_models @staticmethod def _validate_metrics(input_metrics): if not hasattr(input_metrics, "__len__"): raise ValueError( "metrics have to be an array but {}".format(type(input_metrics)) ) valid_metrics = [] for metric in input_metrics: if isinstance(metric, RatingMetric) or isinstance(metric, RankingMetric): valid_metrics.append(metric) return valid_metrics def _create_result(self): from ..eval_methods.cross_validation import CrossValidation if isinstance(self.eval_method, CrossValidation): self.result = CVExperimentResult() else: self.result = ExperimentResult() if self.show_validation and self.eval_method.val_set is not None: self.val_result = ExperimentResult()
[docs] def run(self): """Run the Cornac experiment""" self._create_result() for model in self.models: test_result, val_result = self.eval_method.evaluate( model=model, metrics=self.metrics, user_based=self.user_based, show_validation=self.show_validation, ) self.result.append(test_result) if self.val_result is not None: self.val_result.append(val_result) if not isinstance(self.result, CVExperimentResult): output = "" if self.val_result is not None: output += "\nVALIDATION:\n...\n{}".format(self.val_result) output += "\nTEST:\n...\n{}".format(self.result) print(output) timestamp ="%Y-%m-%d_%H-%M-%S-%f") save_dir = "." if self.save_dir is None else self.save_dir output_file = os.path.join(save_dir, "CornacExp-{}.log".format(timestamp)) with open(output_file, "w") as f: f.write(output)