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Refactor: Rename misspelled function trian_and_predict to train_and_predict #64

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Refactor: Rename misspelled function trian_and_predict to train_and_predict #64

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6 changes: 3 additions & 3 deletions app/services/gaze_tracker.py
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Original file line number Diff line number Diff line change
Expand Up @@ -81,7 +81,7 @@ def squash(v, limit=1.0):
"""Squash não-linear estilo WebGazer"""
return np.tanh(v / limit)

def trian_and_predict(model_name, X_train, y_train, X_test, y_test, label):
def train_and_predict(model_name, X_train, y_train, X_test, y_test, label):
"""
Helper to train a model (with or without GridSearchCV) and return predictions.
"""
Expand Down Expand Up @@ -161,15 +161,15 @@ def predict(data, k, model_X, model_Y):
X_train_x = scaler_x.fit_transform(X_train_x)
X_test_x = scaler_x.transform(X_test_x)

y_pred_x = trian_and_predict(model_X, X_train_x, y_train_x, X_test_x, y_test_x, "X")
y_pred_x = train_and_predict(model_X, X_train_x, y_train_x, X_test_x, y_test_x, "X")

# Scaling (fit on train only)
scaler_y = StandardScaler()
X_train_y = scaler_y.fit_transform(X_train_y)
X_test_y = scaler_y.transform(X_test_y)


y_pred_y = trian_and_predict(model_Y, X_train_y, y_train_y, X_test_y, y_test_y, "Y")
y_pred_y = train_and_predict(model_Y, X_train_y, y_train_y, X_test_y, y_test_y, "Y")

# Convert the predictions to a numpy array and apply KMeans clustering
data = np.array([y_pred_x, y_pred_y]).T
Expand Down