update dllib.py and evaluate.py
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@ -230,10 +230,10 @@ def remove_list(games):
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# features_g = pd.DataFrame(features_g, dtype=np.float64)
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# features_g = features_g.to_numpy()
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platform = pd.read_csv('all_games.train.csv', sep=',', usecols=[1], header=None).values.tolist()
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release_date = pd.read_csv('all_games.train.csv', sep=',', usecols=[2], header=None).values.tolist()
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meta_score = pd.read_csv('all_games.train.csv', sep=',', usecols=[4], header=None).values.tolist()
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user_review = pd.read_csv('all_games.train.csv', sep=',', usecols=[5], header=None).values.tolist()
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platform = pd.read_csv('Data/all_games.train.csv', sep=',', usecols=[1], header=None).values.tolist()
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release_date = pd.read_csv('Data/all_games.train.csv', sep=',', usecols=[2], header=None).values.tolist()
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meta_score = pd.read_csv('Data/all_games.train.csv', sep=',', usecols=[4], header=None).values.tolist()
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user_review = pd.read_csv('Data/all_games.train.csv', sep=',', usecols=[5], header=None).values.tolist()
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games_train = {'platform': platform,
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'release_date': release_date,
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@ -145,10 +145,10 @@ def remove_list(games):
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games['user_review'][i] = games['user_review'][i][0]
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return games
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platform = pd.read_csv('all_games.train.csv', sep=',', usecols=[1], header=None).values.tolist()
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release_date = pd.read_csv('all_games.train.csv', sep=',', usecols=[2], header=None).values.tolist()
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meta_score = pd.read_csv('all_games.train.csv', sep=',', usecols=[4], header=None).values.tolist()
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user_review = pd.read_csv('all_games.train.csv', sep=',', usecols=[5], header=None).values.tolist()
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platform = pd.read_csv('Data/all_games.train.csv', sep=',', usecols=[1], header=None).values.tolist()
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release_date = pd.read_csv('Data/all_games.train.csv', sep=',', usecols=[2], header=None).values.tolist()
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meta_score = pd.read_csv('Data/all_games.train.csv', sep=',', usecols=[4], header=None).values.tolist()
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user_review = pd.read_csv('Data/all_games.train.csv', sep=',', usecols=[5], header=None).values.tolist()
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games_test = {'platform': platform,
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'release_date': release_date,
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