add classifier, improve model naming scheme
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@@ -21,7 +21,7 @@ def freqai_conf(default_conf, tmpdir):
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"strategy": "freqai_test_strat",
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"user_data_dir": Path(tmpdir),
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"strategy-path": "freqtrade/tests/strategy/strats",
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"freqaimodel": "LightGBMPredictionModel",
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"freqaimodel": "LightGBMRegressor",
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"freqaimodel_path": "freqai/prediction_models",
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"timerange": "20180110-20180115",
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"freqai": {
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@@ -43,7 +43,7 @@ def test_train_model_in_series_LightGBM(mocker, freqai_conf):
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def test_train_model_in_series_LightGBMMultiModel(mocker, freqai_conf):
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freqai_conf.update({"timerange": "20180110-20180130"})
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freqai_conf.update({"strategy": "freqai_test_multimodel_strat"})
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freqai_conf.update({"freqaimodel": "LightGBMPredictionMultiModel"})
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freqai_conf.update({"freqaimodel": "LightGBMRegressorMultiTarget"})
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strategy = get_patched_freqai_strategy(mocker, freqai_conf)
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exchange = get_patched_exchange(mocker, freqai_conf)
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strategy.dp = DataProvider(freqai_conf, exchange)
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@@ -73,8 +73,9 @@ def test_train_model_in_series_LightGBMMultiModel(mocker, freqai_conf):
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@pytest.mark.skipif("arm" in platform.uname()[-1], reason="no ARM for Catboost ...")
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def test_train_model_in_series_Catboost(mocker, freqai_conf):
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freqai_conf.update({"timerange": "20180110-20180130"})
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freqai_conf.update({"freqaimodel": "CatboostPredictionModel"})
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del freqai_conf['freqai']['model_training_parameters']['verbosity']
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freqai_conf.update({"freqaimodel": "CatboostRegressor"})
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freqai_conf.get('freqai', {}).update(
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{'model_training_parameters': {"n_estimators": 100, "verbose": 0}})
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strategy = get_patched_freqai_strategy(mocker, freqai_conf)
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exchange = get_patched_exchange(mocker, freqai_conf)
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strategy.dp = DataProvider(freqai_conf, exchange)
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