[FIXED] TypeError: only integer scalar arrays can be converted to a scalar index in python

Issue

im traying to do kfold validation

X = df[['Smedications', 'Infections', 'lib' , 'north']].values

Y= df['Comorbidities'].values

kf = KFold(n_splits=10, shuffle=True)
list(kf.split(X))
splits = list(kf.split(X))
train_indices, test_indices = splits[0]
X_train = X[train_indices]
X_test = X[test_indices]
y_train = y[train_indices]
y_test = y[test_indices]

model = LogisticRegression()
model.fit(X_train, y_train)
print(model.score(X_test, y_test))

but i have error message

TypeError Traceback (most recent call last) in () 12 X_train = X[train_indices] 13 X_test = X[test_indices] ---> 14 y_train = y[train_indices] 15 y_test = y[test_indices] 16

TypeError: only integer scalar arrays can be converted to a scalar index

Solution

Probably you either have arrays that are not numpy or indexes that are not of the int type. If it doesn't work, then show some rows with data X, Y.

X = df[['Smedications', 'Infections', 'lib' , 'north']].values

Y= df['Comorbidities'].values

kf = KFold(n_splits=10, shuffle=True)
list(kf.split(X))
splits = list(kf.split(X))
train_indices, test_indices = splits[0]
X_train = np.array(X)[train_indices.astype(int)]
X_test = np.array(X)[test_indices.astype(int)]
y_train = np.array(y)[train_indices.astype(int)]
y_test = np.array(y)[test_indices.astype(int)]

model = LogisticRegression()
model.fit(X_train, y_train)
print(model.score(X_test, y_test))

Answered By - inquirer