Expected 2D array, got 1D array instead, when using decision tree

Question

I have a data set(19 attributes and 1700 instances),I am training Logistic regression, decision tree, random forest on it. logistic regression works fine but when I try decision trees I get the error:

Expected 2D array, got 1D array instead:
array=[1. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0.
 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 1. 0. 0. 0. 0.
 0. 0. 0. 0. 0. 0. 0. 0. 0.

data = data.interpolate()
print(data.isnull().sum())

data['Year_upd'].fillna('0', inplace=True)
data['Month_upd'].fillna('0', inplace=True)
data['Day_upd'].fillna('0', inplace=True)
data['Hour_upd'].fillna('0', inplace=True)

print(data.isnull().sum())

x = data.drop(labels='Type', axis='columns')
y = data.iloc [:, 13]
x.head()

x_train, x_test, y_train, y_test = train_test_split(x, y ,test_size = 0.2,)
model = LogisticRegression(max_iter = 4000)
model.fit (x_train, y_train)

model3= tree.DecisionTreeClassifier()
model3.fit(x_train,y_train)

I tried using the following code to fix the issue

model3= tree.DecisionTreeClassifier()
model3.fit(x_train.values.reshape(-1, 1),y_train)

and I still get: Number of labels=1424 does not match number of samples=29904

Aaron Keesing · Accepted Answer · 2021-04-19 11:59:05Z

0

x_train should be a 2D features matrix with shape (n_instances, n_features). I would recommend converting the tables to NumPy arrays before splitting and testing, like so:

x = data.drop(labels='Type', axis='columns').to_numpy()
y = data.iloc[:, 13].to_numpy()

# ...
model3= tree.DecisionTreeClassifier()
model3.fit(x_train, y_train)

answered Apr 19, 2021 at 11:59

Aaron Keesing

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6 Comments

Dilpreet Kaur Over a year ago

Hi, I did as you suggested but I still get the same error.

Dilpreet Kaur Over a year ago

Number of labels=1424 does not match number of samples=29904

Aaron Keesing Over a year ago

What are the shapes of x_train and y_train?

Dilpreet Kaur Over a year ago

y_train.shape (1424,) (x_train.shape) (1424, 21)

Aaron Keesing Over a year ago

Then it should be working. Are you still flattening the array or something? Obviously you need to remove the reshape(-1, 1) if that's still present.

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