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Modify rmse function #17

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Modify rmse function #17

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6 changes: 3 additions & 3 deletions eval/mle/mle.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,7 @@
from sklearn.preprocessing import OneHotEncoder, LabelEncoder
from sklearn.tree import DecisionTreeClassifier
from sklearn.metrics import classification_report, accuracy_score, f1_score, precision_score, recall_score, roc_auc_score
from sklearn.metrics import explained_variance_score, mean_squared_error, mean_absolute_error, r2_score
from sklearn.metrics import explained_variance_score, mean_squared_error, mean_absolute_error, r2_score, root_mean_squared_error
from sklearn.model_selection import ParameterGrid
from sklearn.utils._testing import ignore_warnings
from sklearn.exceptions import ConvergenceWarning
Expand Down Expand Up @@ -675,7 +675,7 @@ def _evaluate_regression(train, test, info, val=None):
r2 = r2_score(y_valid, pred)
explained_variance = explained_variance_score(y_valid, pred)
mean_squared = mean_squared_error(y_valid, pred)
root_mean_squared = mean_squared_error(y_valid, pred, squared=False)
root_mean_squared = root_mean_squared_error(y_valid, pred)
mean_absolute = mean_absolute_error(y_valid, pred)

results.append(
Expand Down Expand Up @@ -708,7 +708,7 @@ def _calc(best_model):
r2 = r2_score(y_test, pred)
explained_variance = explained_variance_score(y_test, pred)
mean_squared = mean_squared_error(y_test, pred)
root_mean_squared = mean_squared_error(y_test, pred, squared=False)
root_mean_squared = root_mean_squared_error(y_test, pred)
mean_absolute = mean_absolute_error(y_test, pred)

best_scores.append(
Expand Down